aid stringlengths 9 15 | mid stringlengths 7 10 | abstract stringlengths 78 2.56k | related_work stringlengths 92 1.77k | ref_abstract dict |
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1908.11315 | 2970031230 | Due to its hereditary nature, genomic data is not only linked to its owner but to that of close relatives as well. As a result, its sensitivity does not really degrade over time; in fact, the relevance of a genomic sequence is likely to be longer than the security provided by encryption. This prompts the need for speci... | Long-term security. As the sensitivity of genomic data does not degrade over time, access to an individual's genome poses a threat to her descendants, even years after she has deceased. To the best of our knowledge, GenoGuard @cite_27 is the only attempt to provide long-term security. GenoGuard, reviewed in , relies on... | {
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"We introduce honey encryption (HE), a simple, general approach to encrypting messages using low min-entropy keys such as passwords. HE is designed to produce a ci... |
1908.10896 | 2970353712 | One of the biggest hurdles for customers when purchasing fashion online, is the difficulty of finding products with the right fit. In order to provide a better online shopping experience, platforms need to find ways to recommend the right product sizes and the best fitting products to their customers. These recommendat... | Product fit recommendation has only been researched very recently. The main challenge is to estimate the true size of a product and the best fitting size for a customer, and match them accordingly. This has been handled in a number of different ways. In @cite_18 the true size for customers and products is estimated usi... | {
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"We introduce a hierarchical Bayesian approach to tackle the challenging problem of size recommendation in e-commerce fashion. Our ... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | To extend this notion of distance between @math and @math in , Kantorovich considered a relaxed version in @cite_4 @cite_20 . When an optimal transport map exists, the following second Wasserstein distance recovers . Further, @math is well-defined, even when an optimal transport map might not exist. In particular, it i... | {
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"The following paper is reproduced from a Russian journal of the character of our own Proceedings of the National Academy of Sciences, Comptes Rendus (Doklady) de I'Academie des Sciences de I'URSS, ... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | As there is no easy way to ensure the feasibility of the constraints along the gradient updates, common approach is to translate the optimization into a tractable form, while sacrificing the original goal of finding the optimal transport @cite_25 . Concretely, an entropic or a quadratic regularizer is added to . This m... | {
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"Optimal transport (OT) defines a powerful framework to compare probability distributions in a geometrically faithful way. However, the practical impact of OT is st... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | In this paper, we take a different approach and aim to solve the dual problem, without introducing a regularization. This idea is also considered classically in @cite_12 and more recently in @cite_21 and @cite_11 . The classical approach relies on the exact knowledge of the density, which is not available in practice. ... | {
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"This work builds the connection between the regularity theory of optimal transportation map, Monge-Ampere equation and GANs, which gives a theoretic understanding... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | The idea of solving the semi-dual optimization problem is classically considered in @cite_12 , where the authors derive a formula for the functional derivative of the objective function with respect to @math and propose to solve the optimization problem with the gradient descent method. Their approach is based on the d... | {
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"We present a new, simple, and elegant algorithm for computing the optimal mapping for the Monge-Kantorovich problem with quadratic cost. The method arises from a reformulation of the dual problem into an unconstrained minimization... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | More recently, the authors in @cite_29 @cite_21 propose to learn the function @math in a semi-discrete setting, where one of the marginals is assumed to be a discrete distribution supported on a set of @math points @math , and the other marginal is assumed to have a continuous density with compact convex support @math ... | {
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"In this work, we show the intrinsic relations between optimal transportation and convex geometry, especially the variational approach to solve Alexandrov problem: constructing a convex polytope wi... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | Statistical analysis of learning the optimal transport map through the semi-dual optimization problem is studied in @cite_17 @cite_23 , where the authors establish a minimax convergence rate with respect to number of samples for certain classes of regular probability distributions. They also propose a procedure that ac... | {
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"Isotonic regression is a standard problem in shape-constrained estimation where the goal is to estimate an unknown nondecreasing regression function @math from independent pairs @math where @math ... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | The approach proposed in this paper is built upon the recent work @cite_11 , where the proposal to solve the semi-dual optimization problem by representing the function @math with an ICNN appeared for the first time. The proposed procedure in @cite_11 involves solving a convex optimization problem to compute the convex... | {
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"We provide a framework to approximate the 2-Wasserstein distance and the optimal transport map, amenable to efficient training as well as statistical and geometric analysis. With the quadratic cost and considering the Kantorovich ... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | There are also other alternative approaches to approximate the optimal transport map that are not based on solving the semi-dual optimization problem . @cite_24 , the authors propose to approximate the optimal transport map, through an adversarial computational procedure, by considering the dual optimization problem , ... | {
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"Computing optimal transport maps between high-dimensional and continuous distributions is a challenging problem in optimal transport (OT). Generative adversarial networks (GANs) are powerful genera... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | Another approach, proposed in @cite_22 , is based on a generative learning framework to approximate the optimal coupling, instead of optimal transport map. The approach involves a low-dimensional latent random variable, two generators that take the latent variable as input and map it to a high-dimensional space where t... | {
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"Optimal Transport (OT) naturally arises in many machine learning applications, yet the heavy computational burden limits its wide-spread uses. To address the scalability issue, we propose an impli... |
1908.10962 | 2971222260 | In this paper, we present a novel and principled approach to learn the optimal transport between two distributions, from samples. Guided by the optimal transport theory, we learn the optimal Kantorovich potential which induces the optimal transport map. This involves learning two convex functions, by solving a novel mi... | Finally, a procedure is recently proposed to approximate the optimal transport map that is optimal only on a subspace projection instead of the entire space @cite_1 . This approach is inspired by the sliced Wasserstein distance method to approximate the Wasserstein distance @cite_16 @cite_27 . However, selection of the... | {
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"Generative Adversarial Nets (GANs) are very successful at modeling distributions from given samples, even in the high-dimensional case. However, their formulation ... |
1908.10422 | 2965761667 | Abstract Trainable chatbots that exhibit fluent and human-like conversations remain a big challenge in artificial intelligence. Deep Reinforcement Learning (DRL) is promising for addressing this challenge, but its successful application remains an open question. This article describes a novel ensemble-based approach ap... | black This article contributes to the literature of neural-based chatbots as follows. First, our methodology for training value-based DRL agents uses only unlabelled dialogue data. Previous work requires manual extensions to the dialogue data @cite_13 or expensive and time consuming ratings for training a reward functi... | {
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"We present MILABOT: a deep reinforcement learning chatbot developed by the Montreal Institute for Learning Algorithms (MILA) for the Amazon Alexa Prize competition.... |
1908.10654 | 2970246034 | Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects ( @math ) and modalities ( @math... | Most of existing face anti-spoofing datasets only contain the RGB modality, including the two widely used PAD datasets Replay-Attack @cite_31 and CASIA-FASD @cite_50 . Even the recently released SiW @cite_26 dataset, collected with high resolution image quality, only contains RGB data. With the widespread application o... | {
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1908.10654 | 2970246034 | Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects ( @math ) and modalities ( @math... | As attack techniques are constantly upgraded, some new types of presentation attacks have emerged, , 3D @cite_0 and silicone masks @cite_38 . These attacks are more realistic than traditional 2D attacks. Therefore, the drawbacks of visible cameras are revealed when facing these realistic face masks. Fortunately, some n... | {
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"We investigate the vulnerability of convolutional neural network (CNN) based face-recognition (FR... |
1908.10654 | 2970246034 | Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects ( @math ) and modalities ( @math... | Face anti-spoofing has been studied for decades. Some previous works @cite_34 @cite_51 @cite_1 @cite_53 attempt to detect the evidence of liveness ( , eye-blinking). Another works are based on contextual @cite_7 @cite_9 and moving @cite_22 @cite_44 @cite_57 information. To improve the robustness to illumination variati... | {
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1908.10654 | 2970246034 | Face anti-spoofing is essential to prevent face recognition systems from a security breach. Much of the progresses have been made by the availability of face anti-spoofing benchmark datasets in recent years. However, existing face anti-spoofing benchmarks have limited number of subjects ( @math ) and modalities ( @math... | CNN-based methods @cite_36 @cite_40 @cite_20 @cite_5 @cite_52 @cite_3 have been presented recently in the face PAD community. They treat face PAD as a binary classification problem and achieve remarkable improvements in the intra-testing. Liu al @cite_26 design a network architecture to leverage two auxiliary informati... | {
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1908.10468 | 2971069003 | Knowledge of what spatial elements of medical images deep learning methods use as evidence is important for model interpretability, trustiness, and validation. There is a lack of such techniques for models in regression tasks. We propose a method, called visualization for regression with a generative adversarial networ... | One way to visualize evidence of a class using deep learning is to perform backpropagation of the outputs of a trained classifier @cite_1 . @cite_5 , for example, a model is trained to predict the presence of 14 diseases in chest x-rays, and class activation maps @cite_2 are used to show what regions of the x-rays have... | {
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"We develop an algorithm that can detect pneumonia from chest X-rays at a level exceeding practicing radiologists. Our algorithm, Che... |
1908.10468 | 2971069003 | Knowledge of what spatial elements of medical images deep learning methods use as evidence is important for model interpretability, trustiness, and validation. There is a lack of such techniques for models in regression tasks. We propose a method, called visualization for regression with a generative adversarial networ... | @cite_7 , researchers visualize what brain MRIs of patients with mild cognitive impairment would look like if they developed Alzheimer's disease, generating disease effect maps. To solve problems with other visualization methods, they propose an adversarial setup. A generator is trained to modify an input image which f... | {
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1908.10468 | 2971069003 | Knowledge of what spatial elements of medical images deep learning methods use as evidence is important for model interpretability, trustiness, and validation. There is a lack of such techniques for models in regression tasks. We propose a method, called visualization for regression with a generative adversarial networ... | There have been other works on generating visual attribution for regression. @cite_4 , start by training a GAN on a large dataset of frontal x-rays, and then train an encoder that maps from an x-ray to its latent space vector. Finally, train a small model for regression that receives the latent vector of the images fro... | {
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1908.10398 | 2912215636 | Abstract The deep supervised and reinforcement learning paradigms (among others) have the potential to endow interactive multimodal social robots with the ability of acquiring skills autonomously. But it is still not very clear yet how they can be best deployed in real world applications. As a step in this direction, w... | There is a similarly limited amount of previous work on humanoid robots playing games against human opponents. Notable exceptions include @cite_18 , where the DB humanoid robot learns to play air hockey using a Nearest Neighbour classifier; @cite_9 , where the Nico humanoid torso robot plays the game of rock-paper-scis... | {
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... |
1908.10398 | 2912215636 | Abstract The deep supervised and reinforcement learning paradigms (among others) have the potential to endow interactive multimodal social robots with the ability of acquiring skills autonomously. But it is still not very clear yet how they can be best deployed in real world applications. As a step in this direction, w... | In the remainder of the article we describe a deep learning-based approach for efficiently training a robot with the ability of behaving with reasonable performance in a near real world deployment. In particular, we measure the effectiveness of neural-based game move interpretation and the effectiveness of Deep Q-Netwo... | {
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"An artificial agent is developed that learns to play a diverse range of classic Atari 2600 computer games directly from sensory experience, achieving a performance comparable to that of an expert human player; this work paves the ... |
1908.10357 | 2971237743 | In this paper, we are interested in bottom-up multi-person human pose estimation. A typical bottom-up pipeline consists of two main steps: heatmap prediction and keypoint grouping. We mainly focus on the first step for improving heatmap prediction accuracy. We propose Higher-Resolution Network (HigherHRNet), which is a... | Top-down methods @cite_19 @cite_26 @cite_28 @cite_0 @cite_21 @cite_16 @cite_7 @cite_30 detect a single person keypoints within a person bounding box. The person bounding boxes are usually generated by an object detector @cite_3 @cite_18 @cite_6 . Mask R-CNN @cite_0 directly adds a keypoint detection branch on Faster R-... | {
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1908.10357 | 2971237743 | In this paper, we are interested in bottom-up multi-person human pose estimation. A typical bottom-up pipeline consists of two main steps: heatmap prediction and keypoint grouping. We mainly focus on the first step for improving heatmap prediction accuracy. We propose Higher-Resolution Network (HigherHRNet), which is a... | Bottom-up methods @cite_11 @cite_27 @cite_8 @cite_17 @cite_12 detect identity-free body joints for all the persons in an image and then group them into individuals. OpenPose @cite_17 uses a two-branch multi-stage netork with one branch for heatmap prediction and one branch for grouping. OpenPose uses a grouping method ... | {
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1908.10357 | 2971237743 | In this paper, we are interested in bottom-up multi-person human pose estimation. A typical bottom-up pipeline consists of two main steps: heatmap prediction and keypoint grouping. We mainly focus on the first step for improving heatmap prediction accuracy. We propose Higher-Resolution Network (HigherHRNet), which is a... | There are mainly 4 methods to generate high resolution feature maps. (1) Encoder-decoder @cite_30 @cite_0 @cite_7 @cite_32 @cite_13 @cite_23 @cite_29 captures the context information in the encoder path and recover high resolution features in the decoder path. The decoder usually contains a sequence of bilinear upsampl... | {
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1908.10136 | 2970136826 | Spatial and temporal stream model has gained great success in video action recognition. Most existing works pay more attention to designing effective features fusion methods, which train the two-stream model in a separate way. However, it's hard to ensure discriminability and explore complementary information between d... | Before deep learning became popular, most of the traditional CV algorithm variants apply shallow hand-crafted features to solve action recognition. Improved Dense Trajectories (IDT) @cite_36 which uses densely sampled trajectory features indicates that the temporal information could be processed differently from that o... | {
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1908.10136 | 2970136826 | Spatial and temporal stream model has gained great success in video action recognition. Most existing works pay more attention to designing effective features fusion methods, which train the two-stream model in a separate way. However, it's hard to ensure discriminability and explore complementary information between d... | An activate research which devotes to the design of deep networks for video representation learning has been trying to devise effective ConvNet architectures @cite_40 @cite_3 @cite_19 @cite_3 @cite_23 . @cite_40 attempt to design a deep network which stacks CNN-based frame-level features in a fixed size and then conduc... | {
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1908.10136 | 2970136826 | Spatial and temporal stream model has gained great success in video action recognition. Most existing works pay more attention to designing effective features fusion methods, which train the two-stream model in a separate way. However, it's hard to ensure discriminability and explore complementary information between d... | These works implied the importance of temporal information for action recognition and the incapability of CNNs to capture such information. To exploiting the temporal information, some studies resort to the use of the 3D convolution kernel. @cite_12 @cite_19 apply 3D CNN, both appearance and motion features learned wit... | {
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1908.10136 | 2970136826 | Spatial and temporal stream model has gained great success in video action recognition. Most existing works pay more attention to designing effective features fusion methods, which train the two-stream model in a separate way. However, it's hard to ensure discriminability and explore complementary information between d... | Another efficient way to extract temporal features is to precomputing the optical flow @cite_11 using traditional optical flow estimation methods and training a separate CNN to encode the precomputed optical flow, which is kind of escape from temporal modeling but effective in motion features extraction. The famous two... | {
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1908.10331 | 2953161934 | Training chatbots using the reinforcement learning paradigm is challenging due to high-dimensional states, infinite action spaces and the difficulty in specifying the reward function. We address such problems using clustered actions instead of infinite actions, and a simple but promising reward function based on human-... | Reinforcement Learning (RL) methods are typically based on value functions or policy search @cite_19 , which also applies to deep RL methods. While value functions have been particularly applied to task-oriented dialogue systems @cite_12 @cite_31 @cite_6 @cite_22 @cite_3 @cite_29 , policy search has been particularly a... | {
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1908.10198 | 2970102015 | Event detection is gaining increasing attention in smart cities research. Large-scale mobility data serves as an important tool to uncover the dynamics of urban transportation systems, and more often than not the dataset is incomplete. In this article, we develop a method to detect extreme events in large traffic datas... | The outliers we are interested in this work are due to outliers caused by extreme events. Another related problem considers methods to detect outliers caused by data measurement errors, such as sensor malfunction, malicious tampering, or measurement error @cite_13 @cite_2 @cite_38 . The latter methods can be seen as a ... | {
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1908.10198 | 2970102015 | Event detection is gaining increasing attention in smart cities research. Large-scale mobility data serves as an important tool to uncover the dynamics of urban transportation systems, and more often than not the dataset is incomplete. In this article, we develop a method to detect extreme events in large traffic datas... | Low rank matrix and tensor learning has been widely used to utilize the inner structure of the data. Various application have benefited from matrix and tensor based methods, including data completion @cite_43 @cite_47 , link prediction @cite_33 , network structure clustering @cite_8 , etc. | {
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"Tensor completion is a problem of filling the missing or unobserved entries of partially observed tensors. Due to the multidimensio... |
1908.10198 | 2970102015 | Event detection is gaining increasing attention in smart cities research. Large-scale mobility data serves as an important tool to uncover the dynamics of urban transportation systems, and more often than not the dataset is incomplete. In this article, we develop a method to detect extreme events in large traffic datas... | The most relevant works with ours are robust matrix and tensor PCA for outlier detection. @math norm regularized robust tensor recovery, as proposed by Goldfarb and Qin @cite_46 , is useful when data is polluted with unstructured random noises. @cite_5 also used @math norm regularized tensor decomposition for traffic d... | {
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"Traffic volume data is already collected and used for a variety of purposes in intelligent transportation system (ITS). However, the collected data might be abnormal due to the problem of outlier d... |
1908.10198 | 2970102015 | Event detection is gaining increasing attention in smart cities research. Large-scale mobility data serves as an important tool to uncover the dynamics of urban transportation systems, and more often than not the dataset is incomplete. In this article, we develop a method to detect extreme events in large traffic datas... | In face of large events, outliers tend to group in columns or fibers in the dataset, as illustrated in section . @math norm regularized decomposition is suitable for group outlier detection, as shown in @cite_25 @cite_51 for matrices, and @cite_27 @cite_41 for tensors. In addition, @cite_9 introduced a multi-view low-r... | {
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1908.10193 | 2970619785 | In the field of information retrieval, query expansion (QE) has long been used as a technique to deal with the fundamental issue of word mismatch between a user's query and the target information. In the context of the relationship between the query and expanded terms, existing weighting techniques often fail to approp... | Query expansion has a long history of literature in the field of information retrieval. It was first coined by @cite_29 in the 1960s for literature indexing and searching in a mechanized library system. In 1971, Rocchio @cite_21 brought QE to spotlight through the relevance feedback method and its characterization in a... | {
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"This paper reports on a novel technique for literature indexing and searching in a mechanized library system. The notion of relev... |
1908.10193 | 2970619785 | In the field of information retrieval, query expansion (QE) has long been used as a technique to deal with the fundamental issue of word mismatch between a user's query and the target information. In the context of the relationship between the query and expanded terms, existing weighting techniques often fail to approp... | Based on web search query logs, two types of QE approaches are usually used. The first type extract features from the queries, stored in logs, that are related to the user's original query, with or without making use of their respective retrieval results @cite_43 @cite_20 . In techniques based on the first approach, so... | {
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1908.10193 | 2970619785 | In the field of information retrieval, query expansion (QE) has long been used as a technique to deal with the fundamental issue of word mismatch between a user's query and the target information. In the context of the relationship between the query and expanded terms, existing weighting techniques often fail to approp... | In the context of web-based knowledge, anchor texts can play a role similar to the user's search queries because an anchor text to a page can serve as a brief summary of its content. Anchor texts were first used by McBryan @cite_28 for associating hyperlinks with linked pages as well as with the pages in which the anch... | {
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1908.09775 | 2969344335 | Despite the remarkable success of deep learning in pattern recognition, deep network models face the problem of training a large number of parameters. In this paper, we propose and evaluate a novel multi-path wavelet neural network architecture for image classification with far less number of trainable parameters. The ... | The wavelet transform is a powerful tool for processing data and developing time-frequency representations. A thorough theoretical background on wavelets is explained in @cite_41 @cite_25 . Applying wavelet transform in the context of neural networks is not novel. Earlier work @cite_40 @cite_27 has presented a theoreti... | {
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1908.09826 | 2969846162 | In this paper, we investigate the secure connectivity of wireless sensor networks utilizing the heterogeneous random key predistribution scheme, where each sensor node is classified as class- @math with probability @math for @math with @math and @math . A class- @math sensor is given @math cryptographic keys selected u... | The connectivity (respectively, @math -connectivity) of wireless sensor networks secured by the classical scheme under a uniform on off channel model was investigated in @cite_33 (respectively, @cite_11 ). The network was modeled by a composite random graph formed by the intersection of random key graphs @math (induced... | {
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"We investigate the secure connectivity of wireless sensor networks under the random key distribution scheme of Eschenauer and Gligor. Unlike recent work which was carried out under the assumption ... |
1908.09826 | 2969846162 | In this paper, we investigate the secure connectivity of wireless sensor networks utilizing the heterogeneous random key predistribution scheme, where each sensor node is classified as class- @math with probability @math for @math with @math and @math . A class- @math sensor is given @math cryptographic keys selected u... | In @cite_7 , Ya g an considered the connectivity of wireless sensor networks secured by the heterogeneous random key predistribution scheme under the full visibility assumption, i.e., all wireless channels are available and reliable, hence the only condition for two nodes to be adjacent is to share a key. It is clear t... | {
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"abstract": [
"We introduce a new random key predistribution scheme for securing heterogeneous wireless sensor networks. Each of the @math sensors in the network is classified into @math classes according to some probability distribution @math . ... |
1908.09826 | 2969846162 | In this paper, we investigate the secure connectivity of wireless sensor networks utilizing the heterogeneous random key predistribution scheme, where each sensor node is classified as class- @math with probability @math for @math with @math and @math . A class- @math sensor is given @math cryptographic keys selected u... | In comparison with the existing literature on similar models, our result can be seen to extend the work by Eletreby and Ya g an in @cite_8 (respectively, @cite_18 ). Therein, the authors established a zero-one law for the @math -connectivity (respectively, @math -connectivity) of @math , i.e., for a wireless sensor net... | {
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"We consider secure and reliable connectivity in wireless sensor networks that utilize the heterogeneous random key predistribution scheme. We model the unreliability of wireless links by an on off ... |
1908.10017 | 2970793270 | The state-of-art DNN structures involve intensive computation and high memory storage. To mitigate the challenges, the memristor crossbar array has emerged as an intrinsically suitable matrix computation and low-power acceleration framework for DNN applications. However, the high accuracy solution for extreme model com... | Heuristic weight pruning methods @cite_4 are widely used in neuromorphic computing designs to reduce the weight storage and computing delay @cite_20 . @cite_20 implemented weight pruning techniques on a neuromorphic computing system using irregular pruning caused unbalanced workload, greater circuits overheads and extr... | {
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"abstract": [
"Synapse crossbar is an elementary structure in neuromorphic computing systems (NCS). However, the limited size of crossbars and heavy routing congestion impede the... |
1908.10017 | 2970793270 | The state-of-art DNN structures involve intensive computation and high memory storage. To mitigate the challenges, the memristor crossbar array has emerged as an intrinsically suitable matrix computation and low-power acceleration framework for DNN applications. However, the high accuracy solution for extreme model com... | Weight quantization can mitigate hardware imperfection of memristor including state drift and process variations, caused by the imperfect fabrication process or by the device feature itself @cite_3 @cite_10 . @cite_1 presented a technique to reduce the overhead of Digital-to-Analog Converters (DACs) Analog-to-Digital C... | {
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"abstract": [
"Convolutional Neural Network (CNN) is a powerful technique widely used in computer vision area, which also demands much more computations and memory resources than ... |
1908.09931 | 2971181831 | At present, object recognition studies are mostly conducted in a closed lab setting with classes in test phase typically in training phase. However, real-world problem is far more challenging because: i) new classes unseen in the training phase can appear when predicting; ii) discriminative features need to evolve when... | : Open set recognition was first introduced in @cite_19 , which considers the problem of detecting unseen classes that are never seen in the training phase @cite_2 @cite_27 . Many open-set recognition methods based on SVM @cite_31 @cite_24 and NCM @cite_9 have since been proposed, but all built on shallow models for cl... | {
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1908.09931 | 2971181831 | At present, object recognition studies are mostly conducted in a closed lab setting with classes in test phase typically in training phase. However, real-world problem is far more challenging because: i) new classes unseen in the training phase can appear when predicting; ii) discriminative features need to evolve when... | : different from incremental learning problem, other researchers have proposed tree based classification methods to address the scalability of object categories in large scale visual recognition challenges @cite_6 @cite_10 @cite_18 @cite_4 . Recent advances in the deep learning domain @cite_1 @cite_13 of scalable learn... | {
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"In this work we investigate the effect of the convolutional net... |
1908.09931 | 2971181831 | At present, object recognition studies are mostly conducted in a closed lab setting with classes in test phase typically in training phase. However, real-world problem is far more challenging because: i) new classes unseen in the training phase can appear when predicting; ii) discriminative features need to evolve when... | Open world recognition considers both detection and learning to distinguish the new classes. proposed a NCM learning algorithm that relies on the estimation of a determined threshold in conjunction with the threshold counts on some known new classes @cite_38 . For a more practical situation, proposed an online-learning... | {
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1908.09648 | 2969329859 | This paper is motivated by real-life applications of bi-objective optimization. Having many non dominated solutions, one wishes to cluster the Pareto front using Euclidian distances. The p-center problems, both in the discrete and continuous versions, are proven solvable in polynomial time with a common dynamic program... | Selection or clustering points in PF have been studied with applications to MOO algorithms. Firstly, a motivation is to store representative elements of a large PF (exponential sizes of PF are possible @cite_45 ) for exact methods or population meta-heuristics. Maximizing the quality of discrete representations of Pare... | {
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1908.09648 | 2969329859 | This paper is motivated by real-life applications of bi-objective optimization. Having many non dominated solutions, one wishes to cluster the Pareto front using Euclidian distances. The p-center problems, both in the discrete and continuous versions, are proven solvable in polynomial time with a common dynamic program... | The HSS problem, maximizing the representativity of @math solutions among a PF of size @math , is known to be NP-hard in dimension 3 (and greater) since @cite_10 . An exact algorithm in @math and a polynomial-time approximation scheme for any constant dimension @math are also provided in @cite_10 . The 2d case is solva... | {
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"The hypervolume subset selection problem consists of finding a subset, with a given cardinality k, of a set of nondominated poin... |
1908.09648 | 2969329859 | This paper is motivated by real-life applications of bi-objective optimization. Having many non dominated solutions, one wishes to cluster the Pareto front using Euclidian distances. The p-center problems, both in the discrete and continuous versions, are proven solvable in polynomial time with a common dynamic program... | We note that an affine 2d PF is a line in @math , clustering is equivalent to 1 dimensional cases. 1-dimension K-means was proven to be solvable in polynomial time with a DP algorithm in @math time and @math space. This complexity was improved for a DP algorithm in @math time and @math space in @cite_5 . This is thus t... | {
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"The @math -Means clustering problem on @math points is NP-Hard for any dimension @math , however, for the 1D case there exists exact... |
1908.09485 | 2969944405 | A point-of-interest (POI) recommendation system plays an important role in location-based services (LBS) because it can help people to explore new locations and promote advertisers to launch ads to target users. Exiting POI recommendation methods need users' raw check-in data, which can raise location privacy breaches.... | The problem of successive POI recommendation has received much attention recently @cite_22 @cite_8 @cite_23 @cite_11 . To predict where a user will visit next, we need to consider the relationship between POIs. However, existing private recommendation methods @cite_1 @cite_7 @cite_13 only focus on learning the relation... | {
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1908.09485 | 2969944405 | A point-of-interest (POI) recommendation system plays an important role in location-based services (LBS) because it can help people to explore new locations and promote advertisers to launch ads to target users. Exiting POI recommendation methods need users' raw check-in data, which can raise location privacy breaches.... | Differential privacy @cite_15 is a rigorous privacy standard that requires the output of a DP mechanism should not reveal information specific to any individuals. DP requires a trusted data curator who collects original data from users. Recently, a local version of DP has been proposed. In the local setting, each user ... | {
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1908.09485 | 2969944405 | A point-of-interest (POI) recommendation system plays an important role in location-based services (LBS) because it can help people to explore new locations and promote advertisers to launch ads to target users. Exiting POI recommendation methods need users' raw check-in data, which can raise location privacy breaches.... | There are several works applying DP LDP on the recommendation system @cite_1 @cite_7 @cite_13 . @cite_1 proposed an objective function perturbation method. In their work, a trusted data curator adds Laplace noises to the objective function so that the factorized item matrix satisfies DP. They also proposed a gradient p... | {
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"abstract": [
"Recommender systems are collecting and analyzing user data to provide better user experience. However, several privacy concerns have been raised when a recommender ... |
1908.09550 | 2969760672 | In this paper, we propose a Customizable Architecture Search (CAS) approach to automatically generate a network architecture for semantic image segmentation. The generated network consists of a sequence of stacked computation cells. A computation cell is represented as a directed acyclic graph, in which each node is a ... | Our work is inspired by @cite_0 @cite_35 . Unlike these methods, however, our work attempts to achieve a good tradeoff between system performance and the availability of the computational resource. In other words, our algorithm is optimized with some constraints from real applications. We notice that the recent DPC wor... | {
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"Developing neural network image classification models often requires significant architecture engineering. In this paper,... |
1908.09586 | 2969470403 | Given a hypergraph @math , the Minimum Connectivity Inference problem asks for a graph on the same vertex set as @math with the minimum number of edges such that the subgraph induced by every hyperedge of @math is connected. This problem has received a lot of attention these recent years, both from a theoretical and pr... | This optimization problem is NP-hard @cite_9 , and was first introduced for the design of vacuum systems @cite_5 . It has then be studied independently in several different contexts, mainly dealing with network design: computer networks @cite_1 , social networks @cite_2 (more precisely modeling the communication paradi... | {
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1908.09586 | 2969470403 | Given a hypergraph @math , the Minimum Connectivity Inference problem asks for a graph on the same vertex set as @math with the minimum number of edges such that the subgraph induced by every hyperedge of @math is connected. This problem has received a lot of attention these recent years, both from a theoretical and pr... | Concerning the implementation of algorithms, previous works mainly focused on approximation, greedy and other heuristic techniques @cite_4 . To the best of our knowledge, the first exact algorithm was designed by Agarwal al @cite_17 @cite_7 in the context of structural biology, where the sought graph represents the con... | {
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1908.09586 | 2969470403 | Given a hypergraph @math , the Minimum Connectivity Inference problem asks for a graph on the same vertex set as @math with the minimum number of edges such that the subgraph induced by every hyperedge of @math is connected. This problem has received a lot of attention these recent years, both from a theoretical and pr... | This MILP model was then improved recently by Dar al @cite_12 , who mainly reduced the number of variables and constraints of the formulation, but still representing the connectivity constraints by the means of flows. In addition, they also presented and implemented a number of (already known and new) reduction rules. ... | {
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"abstract": [
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]
} |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Shoulder surfing is a widely known attack in which the adversary tries to infer the victim's authentication secret by looking over his or her shoulder. There is a significant body of research into mitigating the impact of shoulder-surfing attacks. An in-depth survey conducted by @cite_8 considered the threat not only i... | {
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"abstract": [
"A lot of research is being conducted into improving the usability and security of phone-unlocking. There is however a severe lack of scientic data on users’ current unlocking behavior and perceptio... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | PIN keypads and pattern locks are commonly used methods for phone authentication. Unfortunately, these techniques are vulnerable to smudge attacks, because the user leaves oily residues on the screen. Previous work has demonstrated that smudge attacks are especially effective on pattern locks as users drag their finger... | {
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"Touch screens are an increasingly common feature on personal computing devices, especially smartphones, where size and user interface advantages accrue from consolidating multiple hardware components (keyboard, number pad, etc.) i... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Now that smartphones are commonplace, traditional authentication techniques have been adapted to work on the small touchscreens of smartphones. @cite_25 compared speed and shoulder-surfing resistance of a scrambled PIN entry keypad and a normal PIN entry keypad. They found that the scrambled keypad was slower but more ... | {
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"PIN unlock is a popular screen locking mechanism used for protecting the sensitive private information on smart-phones. However, it is susceptible to a number of attacks such as guessing attacks, shoulder surfing attacks, smudge a... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Several works have examined the possibility of augmenting PIN keypads with gestures. SwiPIN, by von @cite_6 , divided the PIN keypad into two sections. Each number in each section corresponded to a different swipe gesture direction. Performing a swipe gesture on the correct section of the screen would insert the corres... | {
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"In this paper, we present SwiPIN, a novel authentication system that allows input of traditional PINs using simple touch gestures like up or down and makes it secure against human observers. We pre... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Other works have looked beyond purely visual representations of PINs by incorporating haptic and audio feedback. @cite_17 created an observation-resistant authentication technique by providing no visual clues to the user. The technique renders a wheel on the screen with identical sections. However, when users drag thei... | {
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"Current standard PIN entry systems for mobile devices are not safe to shoulder surfing. In this paper, we present VibraInput, a two-step PIN entry system based on the combination of vibration and v... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Two-Thumbs-Up (TTU) @cite_9 prevents shoulder-surfing attacks by requiring the user to cover the screen with their hands. This forms a handshield'' and enters a challenge mode. If users move their hands away from the screen, the authentication technique disappears. TTU randomly associates five response'' letters with t... | {
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"Abstract We present a new Personal Identification Number (PIN) entry method for smartphones that can be used in security-critical applications, such as smartphone banking. The proposed “Two-Thumbs-Up” (TTU) scheme is resilient agai... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Harbach at al. @cite_23 focused on comparing PIN locks and pattern locks. They were able to observe the behaviour of 134 smartphone users over one month, revealing differences between the two techniques. Results showed that although pattern locks are faster, users are six times as likely to make mistakes compared to PI... | {
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"To prevent unauthorized parties from accessing data stored on their smartphones, users have the option of enabling a \"lock screen\" that requires a secret code (e.g., PIN, drawing a pattern, or biometric) to gain access to their ... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Another category of PIN entry techniques uses pictures or other graphics. In SemanticLock @cite_10 , users arrange icons on the screen in a memorable way. The user is authenticated based on correct placement of the icons. In a similar work, Awase-E @cite_5 , Takada and Koike leverage photos taken on a user's smartphone... | {
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"There is a trade-off between security and usability in user authentication for mobile phones. Since such devices have a poor input interfaces, 4-digit number passwords are widely used at present. Th... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | There is considerable research exploring whether or not lock screens are even necessary at all, by applying , also known as implicit authentication. Continuous authentication systems analyze an individual's regular patterns of touches on the screen, and build a model. A different user would have different patterns, and... | {
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"We investigate whether a classifier can continuously authenticate users based on the way they interact with the touchscreen of a smart phone. We propose a set of 30 behavioral touch features that c... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Some work has explored applying the principles of continuous authentication to augment traditional lock screen techniques. @cite_12 use spatial touch features in addition to previously used temporal touch features on keyboards to verify users based on their individual text entry behaviours. Examples of spatial touch fe... | {
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"Authentication methods can be improved by considering implicit, individual behavioural cues. In particular, verifying users based on typing behaviour has been widely studied with physical keyboards. On mobile touchscreens, the sam... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Many recent works on touchscreen interactions have started exploring pre-touch information; that is, positional information about the user's hands or fingers before making contact with the screen. For example, with TouchCuts and TouchZoom, @cite_21 used pre-touch finger distance to expand nearby targets on screen, faci... | {
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"Although touch-screen laptops are increasing in popularity, users still do not comfortably rely on touch in these environments, as current software interfaces were not designed for being used by the finger. In this paper, we first... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | Another common application of pre-touch information is for reducing the perceived latency of touchscreen interactions. employed this approach for tabletop displays @cite_4 , achieving a touch location prediction error of about 1 ,cm. The approach was implemented by tracking the user's index finger location using motion... | {
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"A method of reducing the perceived latency of touch input by employing a model to predict touch events before the finger reaches the touch surface is proposed. A corpus of 3D finger movement data was collected, and used to develop ... |
1908.09165 | 2969385932 | Smartphones store a significant amount of personal and private information, and are playing an increasingly important role in people's lives. It is important for authentication techniques to be more resistant against two known attacks called shoulder surfing and smudge attacks. In this work, we propose a new technique ... | We anticipate pre-touch sensing to become available on commodity smartphones in the near future. In 2016, @cite_2 explored how a smartphone with a self-capacitance touchscreen could enable pre-touch information to be sensed, and applied this information in various smartphone applications. We envision that our pre-touch... | {
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"Touchscreens continue to advance including progress towards sensing fingers proximal to the display. We explore this emerging pre-touch modality via a self-capacitance touchscreen that can sense multiple fingers above a mobile devi... |
1908.09340 | 2969469636 | This paper mainly studies one-example and few-example video person re-identification. A multi-branch network PAM that jointly learns local and global features is proposed. PAM has high accuracy, few parameters and converges fast, which is suitable for few-example person re-identification. We iteratively estimates label... | In the first type, @cite_8 propose a framework for solving the problem of one-shot classification. They first build a fully convolutional siamese network based on verification loss, and then use this network to calculate the similarity between the image to be identified and other labeled samples. The image is then reco... | {
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"In this paper, we investigate the challenging task of person re-identification from a new perspective and propose an end-to-end attention-based architecture for few-shot re-i... |
1908.09340 | 2969469636 | This paper mainly studies one-example and few-example video person re-identification. A multi-branch network PAM that jointly learns local and global features is proposed. PAM has high accuracy, few parameters and converges fast, which is suitable for few-example person re-identification. We iteratively estimates label... | In the second type, @cite_9 establish a graph for each camera. They view the labeled sample as the node of the graph, and view the distance between the video sequence features as the path. Unlabeled sample are mapped into different graphs (namely estimating the labels) to minimize the objective function. The graphs are... | {
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"Label estimation is an important component in an unsupervised person re-identification (re-ID) system. This paper focuses on cross-camera label estimation, which ca... |
1908.09072 | 2969789183 | Accurate camera pose estimation result is essential for visual SLAM (VSLAM). This paper presents a novel pose correction method to improve the accuracy of the VSLAM system. Firstly, the relationship between the camera pose estimation error and bias values of map points is derived based on the optimized function in VSLA... | A monocular SLAM system, which leverages structural regularity in Manhattan world and contains three optimization strategies is proposed in @cite_17 . However, to reduce the estimation error of the rotation motion, multiple orthogonal planes must be visible throughout the entire motion estimation process. Unlike only u... | {
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"We present a low-drift visual odometry algorithm that separately estimates rotational and translational motion from lines, planes... |
1908.08972 | 2969766398 | Deep Neural Networks (DNNs) have achieved state-of-the-art accuracy performance in many tasks. However, recent works have pointed out that the outputs provided by these models are not well-calibrated, seriously limiting their use in critical decision scenarios. In this work, we propose to use a decoupled Bayesian stage... | On the side of BNNs, @cite_18 connect Bernoulli dropout with BNNs, and @cite_29 formalize Gaussian dropout as a Bayesian approach. In @cite_5 , novel BNNs are proposed, using RealNVP @cite_22 to implement a normalizing flow @cite_56 , auxiliary variables and local reparameterization . None of these approaches measure c... | {
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... |
1908.08994 | 2969915736 | Text detection in natural images is a challenging but necessary task for many applications. Existing approaches utilize large deep convolutional neural networks making it difficult to use them in real-world tasks. We propose a small yet relatively precise text extraction method. The basic component of it is a convoluti... | Since the implementation of deep learning became practical, text detection techniques are based on neural networks. A deep learning based method @cite_2 uses fully convolutional network (FCN) to find a probability that pixels belong to a text area. After applying maximally stable extremal regions (MSER), a shortened FC... | {
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"In this paper, we propose a novel approach for text detection in natural images. Both local and global cues are taken into account for localizing text lines in a coarse-to-fine procedure. First, a Fully Convolutional Network (FCN) ... |
1908.08994 | 2969915736 | Text detection in natural images is a challenging but necessary task for many applications. Existing approaches utilize large deep convolutional neural networks making it difficult to use them in real-world tasks. We propose a small yet relatively precise text extraction method. The basic component of it is a convoluti... | Shi in @cite_4 proposed to find segments of words and connections between them. The whole detection process of segments and links was done in a single pass of a CNN named SegLink in a fully-convolutional manner with depth-first search (DFS) and bounding box creation postprocessing. | {
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"Most state-of-the-art text detection methods are specific to horizontal Latin text and are not fast enough for real-time applications. We introduce Segment Linking (SegLink), an oriented text detection method. The main idea is to d... |
1908.08994 | 2969915736 | Text detection in natural images is a challenging but necessary task for many applications. Existing approaches utilize large deep convolutional neural networks making it difficult to use them in real-world tasks. We propose a small yet relatively precise text extraction method. The basic component of it is a convoluti... | Zhou proposed a similar strategy in @cite_3 where a variety of postprocessing steps were eliminated by performing most of the calculations in a single U-Net-like @cite_12 FCN named EAST which outputs word box parameters by itself. Results of computations are filtered by non-maximum suppression (NMS) and thresholding. T... | {
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"There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the stro... |
1908.08994 | 2969915736 | Text detection in natural images is a challenging but necessary task for many applications. Existing approaches utilize large deep convolutional neural networks making it difficult to use them in real-world tasks. We propose a small yet relatively precise text extraction method. The basic component of it is a convoluti... | An ArbiText network @cite_8 based on the Single Shot Detector (SSD) applies the circle anchors to replace bounding boxes which should be more robust to orientation variations. Authors also applied pyramid pooling to preserve low-level features in deeper layers. | {
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"Arbitrary-oriented text detection in the wild is a very challenging task, due to the aspect ratio, scale, orientation, and illumination variations. In this paper, we propose a novel method, namely Arbitrary-oriented Text (or ArbTex... |
1908.08994 | 2969915736 | Text detection in natural images is a challenging but necessary task for many applications. Existing approaches utilize large deep convolutional neural networks making it difficult to use them in real-world tasks. We propose a small yet relatively precise text extraction method. The basic component of it is a convoluti... | Liu in @cite_13 combined text detection and recognition parts in one end-to-end CNN. The backbone of the network is the Feature Pyramid Network which incorporates residual operations from ResNet-50 @cite_15 . The network, in text detection part, outputs text probability, bounding box distances in four directions, and a... | {
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"Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously. We explicitl... |
1908.08979 | 2969556441 | Various psychological factors affect how individuals express emotions. Yet, when we collect data intended for use in building emotion recognition systems, we often try to do so by creating paradigms that are designed just with a focus on eliciting emotional behavior. Algorithms trained with these types of data are unli... | One group of methods have considered confounding factors that are either singularly labeled or cannot be labeled. Ben-David et. al @cite_49 showed that a classifier trained to predict the sentiment of reviews can implicitly learn to predict the category of the products. The authors used an adversarial multi-task classi... | {
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"The performance of speech emotion recognition is affected by the differences in data distributions between train (source domain) and test (target domain) sets use... |
1908.08909 | 2969984239 | Predicting features of complex, large-scale quantum systems is essential to the characterization and engineering of quantum architectures. We present an efficient approach for predicting a large number of linear features using classical shadows obtained from very few quantum measurements. This approach is guaranteed to... | The task of reconstructing a full classical description -- the density matrix @math -- of a @math -dimensional quantum system from experimental data is one of the most fundamental problems in quantum statistics, see e.g. @cite_52 @cite_13 @cite_12 @cite_31 and references therein. Sample-optimal protocols, i.e. estimati... | {
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1908.08909 | 2969984239 | Predicting features of complex, large-scale quantum systems is essential to the characterization and engineering of quantum architectures. We present an efficient approach for predicting a large number of linear features using classical shadows obtained from very few quantum measurements. This approach is guaranteed to... | Restricting attention to highly structured subsets of quantum states sometimes allows for overcoming the exponential bottleneck that plagues general tomography. Matrix product state (MPS) tomography @cite_41 is the most prominent example for such an approach. It only requires a polynomial number of samples, provided th... | {
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"Direct quantum state tomography—deducing the state of a system from measurements—is mostly unfeasible due to the exponential scaling of measurement number with system size. The authors present two... |
1908.08909 | 2969984239 | Predicting features of complex, large-scale quantum systems is essential to the characterization and engineering of quantum architectures. We present an efficient approach for predicting a large number of linear features using classical shadows obtained from very few quantum measurements. This approach is guaranteed to... | Direct fidelity estimation is a procedure that allows for predicting a single pure target fidelity @math up to accuracy @math . The best-known technique is based on few Pauli measurements that are selected randomly using importance sampling @cite_49 . The required number of samples depends on the target: it can range f... | {
"cite_N": [
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"We describe a simple method for certifying that an experimental device prepares a desired quantum state ρ. Our method is applicable to any pure state ρ, and it provides an estimate of the fidelity between ρ and the actual (arbitra... |
1908.08909 | 2969984239 | Predicting features of complex, large-scale quantum systems is essential to the characterization and engineering of quantum architectures. We present an efficient approach for predicting a large number of linear features using classical shadows obtained from very few quantum measurements. This approach is guaranteed to... | Shadow tomography aims at simultaneously estimating the probability associated with @math 2-outcome measurements up to accuaracy @math : @math , where each @math is a positive semidefinite matrix whose with operator norm at most one @cite_15 @cite_5 @cite_47 . This may be viewed as a generalization of direct fidelity e... | {
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"abstract": [
"We give two new quantum algorithms for solving semidefinite programs (SDPs) providing quantum speed-ups. We consider SDP instances with @math constraint matrices, ... |
1908.08474 | 2969551072 | The Shapley value has become a popular method to attribute the prediction of a machine-learning model on an input to its base features. The Shapley value [1] is known to be the unique method that satisfies certain desirable properties, and this motivates its use. Unfortunately, despite this uniqueness result, there are... | The first and second approaches solve a different problem (of feature importance across all the training data), and we will ignore them for the most part. Notice that the rest are solving the attribution problem, @cite_13 unifies several of these methods under a common framework based on conditional expectations. and t... | {
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"Understanding why a model makes a certain prediction can be as crucial as the prediction's accuracy in many applications. However, the highest accuracy for large modern datasets is often achieved by complex models that even expert... |
1908.08692 | 2969835258 | Automatic estimation of the number of people in unconstrained crowded scenes is a challenging task and one major difficulty stems from the huge scale variation of people. In this paper, we propose a novel Deep Structured Scale Integration Network (DSSINet) for crowd counting, which addresses the scale variation of peop... | Crowd Counting: Numerous deep learning based methods @cite_33 @cite_13 @cite_20 @cite_40 @cite_46 @cite_6 @cite_10 have been proposed for crowd counting. These methods have various network structures and the mainstream is a multiscale architecture, which extracts multiple features from different columns branches of net... | {
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1908.08692 | 2969835258 | Automatic estimation of the number of people in unconstrained crowded scenes is a challenging task and one major difficulty stems from the huge scale variation of people. In this paper, we propose a novel Deep Structured Scale Integration Network (DSSINet) for crowd counting, which addresses the scale variation of peop... | Conditional Random Fields: In the field of computer vision, CRFs have been exploited to refine the features and outputs of convolutional neural networks (CNN) with a message passing mechanism @cite_25 . For instance, @cite_29 used CRFs to refine the semantic segmentation maps of CNN by modeling the relationship among p... | {
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"Recent works have shown that exploiting multi-scale representations deeply learned via convolutional neural networks (CNN) is of... |
1908.08692 | 2969835258 | Automatic estimation of the number of people in unconstrained crowded scenes is a challenging task and one major difficulty stems from the huge scale variation of people. In this paper, we propose a novel Deep Structured Scale Integration Network (DSSINet) for crowd counting, which addresses the scale variation of peop... | Multiscale Structural Similarity: MS-SSIM @cite_37 is a widely used metric for image quality assessment. Its formula is based on the luminance, contrast and structure comparisons between the multiscale regions of two images. In @cite_22 , MS-SSIM loss has been successfully applied in image restoration tasks (e.g., imag... | {
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1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | The whole concept of adversarial attacks is quite simple: let us slightly change the input to a classifying neural net so that the recognized class will change from correct to some other class (first adversarial attacks were made only on classifiers). The pioneering work @cite_27 formulates the task as follows: | {
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1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | In @cite_27 the authors propose to use a quasi-newton L-BFGS-B method to solve the task formulated above. Simpler and more efficient method called Fast Gradient-Sign Method (FGSM) is proposed in @cite_39 . This method suggests using the gradients with respect to the input and constructing an adversarial image using the... | {
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"Deep neural networks are highly expressive models that have recently achieved state of the art performance on speech and visual recognition tasks. While their exp... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | It turns out that using momentum for the iterative procedure of an adversarial example construction is a good way to increase the robustness of the adversarial attack @cite_17 . | {
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"Deep neural networks are vulnerable to adversarial examples, which poses security concerns on these algorithms due to the potentially severe consequences. Adversarial attacks serve as an important surrogate to evaluate the robustn... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | All the aforementioned adversarial attacks suggest that we restrict the maximum per-pixel perturbation (in case of image as an input) i.e. use @math norm. Another interesting case is when we do not concentrate on the maximum perturbation but we strive to achieve the fewest possible number of pixels to be attacked ( @ma... | {
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1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | Another extreme case of attack for the @math norm is a one-pixel attack @cite_0 . The authors use differential evolution for this specific case, the algorithm which lies in the class of evolutionary algorithms. It should be mentioned that not only classification neural nets are prone to adversarial attacks. There are a... | {
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"Recent research has revealed that the output of Deep Neural Networks (DNN) can be easily altered by adding relatively small perturbations to the input vector. In this paper, we analyze an attack in... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | Another interesting property of the adversarial attacks is that they are transferable between different neural networks @cite_27 . An attack prepared using one model can successfully confuse another model with different architecture and training dataset. | {
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"Deep neural networks are highly expressive models that have recently achieved state of the art performance on speech and visual recognition tasks. While their expressiveness is the reason they succeed, it also causes them to learn... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | Usually, the adversarial attacks which are constructed using the specific architecture and even the weights of the attacked model are called white-box attacks. If the attack has no access to model weights then it is called a black-box attack @cite_36 . | {
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"Machine learning (ML) models, e.g., deep neural networks (DNNs), are vulnerable to adversarial examples: malicious inputs modified to yield erroneous model outputs, while appearing unmodified to human observers. Potential attacks ... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | Usually, attacks are constructed for the specific input (e.g. photo of some object). This is called an input-aware attack. Adversarial attacks are called universal when one successful adversarial perturbation can be applied for any image @cite_23 . | {
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"@cite_23"
],
"mid": [
"2953047670"
],
"abstract": [
"Given a state-of-the-art deep neural network classifier, we show the existence of a universal (image-agnostic) and very small perturbation vector that causes natural images to be misclassified with high probability. We propose a s... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | Although adversarial attacks are quite successful in the digital domain (where we can change the image on the pixel level before feeding it to a classifier), in the physical (i.e. real) world the efficiency of adversarial attacks is still questionable. Kurakin demonstrate the potential for further research in this doma... | {
"cite_N": [
"@cite_5"
],
"mid": [
"2460937040"
],
"abstract": [
"Most existing machine learning classifiers are highly vulnerable to adversarial examples. An adversarial example is a sample of input data which has been modified very slightly in a way that is intended to cause a machine learning ... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | It turns out that the most successful paradigm to construct the real-world adversarial examples is an Expectation Over Transformation (EOT) algorithm @cite_28 . This approach takes into account that in the real world the object usually undergoes a set of transformations (scaling, jittering, brightness and contrast chan... | {
"cite_N": [
"@cite_28"
],
"mid": [
"2736899637"
],
"abstract": [
"Standard methods for generating adversarial examples for neural networks do not consistently fool neural network classifiers in the physical world due to a combination of viewpoint shifts, camera noise, and other natural transform... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | Another work with the usage of @math -limited attacks proposes to attack facial recognition neural nets with the adversarial eyeglasses @cite_21 . The authors propose a method to print adversarial perturbation on the eyeglasses frame with the help of Total Variation (TV) loss and non-printability score (NPS). TV loss i... | {
"cite_N": [
"@cite_21"
],
"mid": [
"2535873859"
],
"abstract": [
"Machine learning is enabling a myriad innovations, including new algorithms for cancer diagnosis and self-driving cars. The broad use of machine learning makes it important to understand the extent to which machine-learning algori... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | In general, most of the subsequent works for the real-world attack use the concepts of @math -limited perturbation, EOT, TV loss, and NPS. Let us briefly list them. In @cite_40 the authors construct the physical attack for the traffic sign recognition model using EOT and NPS for making either adversarial posters (attac... | {
"cite_N": [
"@cite_40",
"@cite_1",
"@cite_15"
],
"mid": [
"2759471388",
"2783882201",
""
],
"abstract": [
"Recent studies show that the state-of-the-art deep neural networks (DNNs) are vulnerable to adversarial examples, resulting from small-magnitude perturbations added to the i... |
1908.08705 | 2969664989 | In this paper we propose a novel easily reproducible technique to attack the best public Face ID system ArcFace in different shooting conditions. To create an attack, we print the rectangular paper sticker on a common color printer and put it on the hat. The adversarial sticker is prepared with a novel algorithm for of... | A number of works are devoted to adversarial attacks on traffic sign detectors in the real world. One of the first works @cite_22 proposes an adversarial attack on Faster R-CNN @cite_35 stop sign detector using a sort of EOT (handcrafted estimation of a viewing map). Several works used EOT, NPS, and TV loss to attack F... | {
"cite_N": [
"@cite_35",
"@cite_22",
"@cite_8",
"@cite_42",
"@cite_19",
"@cite_45"
],
"mid": [
"2953106684",
"2775467454",
"",
"2951433694",
"2890883923",
"2778115935"
],
"abstract": [
"State-of-the-art object detection networks depend on region proposal al... |
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