paper_id stringlengths 10 10 | paper_url stringlengths 37 80 | title stringlengths 4 518 | abstract stringlengths 3 7.27k | arxiv_id stringlengths 9 16 ⌀ | url_abs stringlengths 18 601 | url_pdf stringlengths 21 601 | aspect_tasks list | aspect_methods list | aspect_datasets list |
|---|---|---|---|---|---|---|---|---|---|
JcLcErsT3A | https://paperswithcode.com/paper/unsupervised-topic-modeling-approaches-to | Unsupervised Topic Modeling Approaches to Decision Summarization in Spoken Meetings | We present a token-level decision summarization framework that utilizes the
latent topic structures of utterances to identify "summary-worthy" words.
Concretely, a series of unsupervised topic models is explored and experimental
results show that fine-grained topic models, which discover topics at the
utterance-level r... | 1606.07829 | http://arxiv.org/abs/1606.07829v1 | http://arxiv.org/pdf/1606.07829v1.pdf | [
"Decision Making",
"Topic Models"
] | [] | [] |
XaIuQeCcrU | https://paperswithcode.com/paper/neural-inverse-rendering-for-general | Neural Inverse Rendering for General Reflectance Photometric Stereo | We present a novel convolutional neural network architecture for photometric
stereo (Woodham, 1980), a problem of recovering 3D object surface normals from
multiple images observed under varying illuminations. Despite its long history
in computer vision, the problem still shows fundamental challenges for surfaces
with ... | 1802.10328 | http://arxiv.org/abs/1802.10328v2 | http://arxiv.org/pdf/1802.10328v2.pdf | [] | [] | [] |
yW5Kx_2y7v | https://paperswithcode.com/paper/properties-of-phoneme-n-grams-across-the | Properties of phoneme N -grams across the world's language families | In this article, we investigate the properties of phoneme N-grams across half
of the world's languages. We investigate if the sizes of three different N-gram
distributions of the world's language families obey a power law. Further, the
N-gram distributions of language families parallel the sizes of the families,
which ... | 1401.0794 | http://arxiv.org/abs/1401.0794v1 | http://arxiv.org/pdf/1401.0794v1.pdf | [] | [] | [] |
ejM4XgukeC | https://paperswithcode.com/paper/deep-reinforcement-learning-with-relational | Deep reinforcement learning with relational inductive biases | We introduce an approach for augmenting model-free deep reinforcement learning agents with a mechanism for relational reasoning over structured representations, which improves performance, learning efficiency, generalization, and interpretability. Our architecture encodes an image as a set of vectors, and applies an it... | null | https://openreview.net/forum?id=HkxaFoC9KQ | https://openreview.net/pdf?id=HkxaFoC9KQ | [
"Relational Reasoning",
"Starcraft",
"Starcraft II"
] | [] | [] |
iKWtjuR001 | https://paperswithcode.com/paper/generalized-byzantine-tolerant-sgd | Generalized Byzantine-tolerant SGD | We propose three new robust aggregation rules for distributed synchronous
Stochastic Gradient Descent~(SGD) under a general Byzantine failure model. The
attackers can arbitrarily manipulate the data transferred between the servers
and the workers in the parameter server~(PS) architecture. We prove the
Byzantine resilie... | 1802.10116 | http://arxiv.org/abs/1802.10116v3 | http://arxiv.org/pdf/1802.10116v3.pdf | [] | [] | [] |
N15l-ypYs9 | https://paperswithcode.com/paper/arabic-language-text-classification-using | Arabic Language Text Classification Using Dependency Syntax-Based Feature Selection | We study the performance of Arabic text classification combining various
techniques: (a) tfidf vs. dependency syntax, for feature selection and
weighting; (b) class association rules vs. support vector machines, for
classification. The Arabic text is used in two forms: rootified and lightly
stemmed. The results we obta... | 1410.4863 | http://arxiv.org/abs/1410.4863v1 | http://arxiv.org/pdf/1410.4863v1.pdf | [
"Feature Selection",
"Text Classification"
] | [] | [] |
BK2oiT5Bp5 | https://paperswithcode.com/paper/identifying-short-term-interests-from-mobile | Identifying short-term interests from mobile app adoption pattern | With the increase in an average user's dependence on their mobile devices,
the reliance on collecting his browsing history from mobile browsers has also
increased. This browsing history is highly utilized in the advertising industry
for providing targeted ads in the purview of inferring his short-term interests
and pus... | 1904.11388 | http://arxiv.org/abs/1904.11388v1 | http://arxiv.org/pdf/1904.11388v1.pdf | [] | [] | [] |
ahuqmSCGP_ | https://paperswithcode.com/paper/applying-naive-bayes-classification-to-google | Applying Naive Bayes Classification to Google Play Apps Categorization | There are over one million apps on Google Play Store and over half a million
publishers. Having such a huge number of apps and developers can pose a
challenge to app users and new publishers on the store. Discovering apps can be
challenging if apps are not correctly published in the right category, and, in
turn, reduce... | 1608.08574 | http://arxiv.org/abs/1608.08574v1 | http://arxiv.org/pdf/1608.08574v1.pdf | [
"Document Classification",
"Sentiment Analysis"
] | [] | [] |
-KZNTKpIN7 | https://paperswithcode.com/paper/etymological-wordnet-tracing-the-history-of | Etymological Wordnet: Tracing The History of Words | Research on the history of words has led to remarkable insights about language and also about the history of human civilization more generally. This paper presents the Etymological Wordnet, the first database that aims at making word origin information available as a large, machine-readable network of words in many lan... | null | https://www.aclweb.org/anthology/L14-1063/ | http://www.lrec-conf.org/proceedings/lrec2014/pdf/1083_Paper.pdf | [] | [] | [] |
vWvMrCwLG6 | https://paperswithcode.com/paper/realizing-half-diminished-reality-from-video | Realizing Half-Diminished Reality from Video Stream of Manipulating Objects | When we watch a video, in which human hands manipulate objects, these hands
may obscure some parts of those objects. We are willing to make clear how the
objects are manipulated by making the image of hands semi-transparent, and
showing the complete images of the hands and the object. By carefully choosing
a Half-Dimin... | 1709.08340 | http://arxiv.org/abs/1709.08340v1 | http://arxiv.org/pdf/1709.08340v1.pdf | [] | [] | [] |
x6RWq1D_j0 | https://paperswithcode.com/paper/learning-with-fredholm-kernels | Learning with Fredholm Kernels | In this paper we propose a framework for supervised and semi-supervised learning based on reformulating the learning problem as a regularized Fredholm integral equation. Our approach fits naturally into the kernel framework and can be interpreted as constructing new data-dependent kernels, which we call Fredholm kernel... | null | http://papers.nips.cc/paper/5237-learning-with-fredholm-kernels | http://papers.nips.cc/paper/5237-learning-with-fredholm-kernels.pdf | [] | [] | [] |
SP5YIDgZa- | https://paperswithcode.com/paper/sequential-neural-methods-for-likelihood-free | Sequential Neural Methods for Likelihood-free Inference | Likelihood-free inference refers to inference when a likelihood function
cannot be explicitly evaluated, which is often the case for models based on
simulators. Most of the literature is based on sample-based `Approximate
Bayesian Computation' methods, but recent work suggests that approaches based
on deep neural condi... | 1811.08723 | http://arxiv.org/abs/1811.08723v1 | http://arxiv.org/pdf/1811.08723v1.pdf | [] | [] | [] |
5HW0dPNFj4 | https://paperswithcode.com/paper/asynchronous-advantage-actor-critic-agent-for | Asynchronous Advantage Actor-Critic Agent for Starcraft II | Deep reinforcement learning, and especially the Asynchronous Advantage
Actor-Critic algorithm, has been successfully used to achieve super-human
performance in a variety of video games. Starcraft II is a new challenge for
the reinforcement learning community with the release of pysc2 learning
environment proposed by Go... | 1807.08217 | http://arxiv.org/abs/1807.08217v1 | http://arxiv.org/pdf/1807.08217v1.pdf | [
"Starcraft",
"Starcraft II",
"Transfer Learning"
] | [] | [] |
pljjNOCyjC | https://paperswithcode.com/paper/population-contrastive-divergence-does | Population-Contrastive-Divergence: Does Consistency help with RBM training? | Estimating the log-likelihood gradient with respect to the parameters of a
Restricted Boltzmann Machine (RBM) typically requires sampling using Markov
Chain Monte Carlo (MCMC) techniques. To save computation time, the Markov
chains are only run for a small number of steps, which leads to a biased
estimate. This bias ca... | 1510.01624 | http://arxiv.org/abs/1510.01624v4 | http://arxiv.org/pdf/1510.01624v4.pdf | [] | [] | [] |
1x9IQ_84SK | https://paperswithcode.com/paper/quantum-medical-imaging-algorithms | Quantum Medical Imaging Algorithms | A central task in medical imaging is the reconstruction of an image or function from data collected by medical devices (e.g., CT, MRI, and PET scanners). We provide quantum algorithms for image reconstruction that can offer exponential speedup over classical counterparts when data is fed into the algorithm as a quantum... | 2004.02036 | https://arxiv.org/abs/2004.02036v1 | https://arxiv.org/pdf/2004.02036v1.pdf | [
"Image Reconstruction"
] | [] | [] |
DzekgShXLd | https://paperswithcode.com/paper/learning-nonparametric-forest-graphical | Learning Nonparametric Forest Graphical Models with Prior Information | We present a framework for incorporating prior information into nonparametric
estimation of graphical models. To avoid distributional assumptions, we
restrict the graph to be a forest and build on the work of forest density
estimation (FDE). We reformulate the FDE approach from a Bayesian perspective,
and introduce pri... | 1511.03796 | http://arxiv.org/abs/1511.03796v2 | http://arxiv.org/pdf/1511.03796v2.pdf | [
"Density Estimation"
] | [] | [] |
EzZlwZX_3L | https://paperswithcode.com/paper/relational-reasoning-using-prior-knowledge | Relational Reasoning using Prior Knowledge for Visual Captioning | Exploiting relationships among objects has achieved remarkable progress in interpreting images or videos by natural language. Most existing methods resort to first detecting objects and their relationships, and then generating textual descriptions, which heavily depends on pre-trained detectors and leads to performance... | 1906.01290 | https://arxiv.org/abs/1906.01290v1 | https://arxiv.org/pdf/1906.01290v1.pdf | [
"Image Captioning",
"Object Detection",
"Relational Reasoning",
"Video Captioning"
] | [] | [] |
yODSiFvyts | https://paperswithcode.com/paper/bridging-stereo-matching-and-optical-flow-via-1 | Bridging Stereo Matching and Optical Flow via Spatiotemporal Correspondence | Stereo matching and flow estimation are two essential tasks for scene understanding, spatially in 3D and temporally in motion. Existing approaches have been focused on the unsupervised setting due to the limited resource to obtain the large-scale ground truth data. To construct a self-learnable objective, co-related ta... | 1905.09265 | https://arxiv.org/abs/1905.09265v1 | https://arxiv.org/pdf/1905.09265v1.pdf | [
"Optical Flow Estimation",
"Scene Understanding",
"Stereo Matching",
"Stereo Matching Hand"
] | [] | [] |
ISAElOuhdv | https://paperswithcode.com/paper/deeplung-3d-deep-convolutional-nets-for | DeepLung: 3D Deep Convolutional Nets for Automated Pulmonary Nodule Detection and Classification | In this work, we present a fully automated lung CT cancer diagnosis system,
DeepLung. DeepLung contains two parts, nodule detection and classification.
Considering the 3D nature of lung CT data, two 3D networks are designed for the
nodule detection and classification respectively. Specifically, a 3D Faster
R-CNN is des... | 1709.05538 | http://arxiv.org/abs/1709.05538v1 | http://arxiv.org/pdf/1709.05538v1.pdf | [
"Automated Pulmonary Nodule Detection And Classification"
] | [] | [] |
n05ytJvpcU | https://paperswithcode.com/paper/a-random-matrix-perspective-on-mixtures-of-1 | A Random Matrix Perspective on Mixtures of Nonlinearities for Deep Learning | One of the distinguishing characteristics of modern deep learning systems is that they typically employ neural network architectures that utilize enormous numbers of parameters, often in the millions and sometimes even in the billions. While this paradigm has inspired significant research on the properties of large net... | 1912.00827 | https://arxiv.org/abs/1912.00827v1 | https://arxiv.org/pdf/1912.00827v1.pdf | [] | [] | [] |
K9z0USdozM | https://paperswithcode.com/paper/test-positive-at-w-nut-2020-shared-task-3 | TEST_POSITIVE at W-NUT 2020 Shared Task-3: Joint Event Multi-task Learning for Slot Filling in Noisy Text | The competition of extracting COVID-19 events from Twitter is to develop systems that can automatically extract related events from tweets. The built system should identify different pre-defined slots for each event, in order to answer important questions (e.g., Who is tested positive? What is the age of the person? Wh... | 2009.14262 | https://arxiv.org/abs/2009.14262v1 | https://arxiv.org/pdf/2009.14262v1.pdf | [
"Language Modelling",
"Multi-Task Learning",
"Named Entity Recognition",
"Slot Filling"
] | [
"Adam",
"Softmax",
"GELU",
"Dense Connections",
"Dropout",
"Linear Warmup With Linear Decay",
"Layer Normalization",
"Attention Dropout",
"WordPiece",
"Multi-Head Attention",
"Weight Decay",
"Scaled Dot-Product Attention",
"Residual Connection",
"BERT"
] | [] |
ERfshFUmN6 | https://paperswithcode.com/paper/global-variational-method-for-fingerprint | Global Variational Method for Fingerprint Segmentation by Three-part Decomposition | Verifying an identity claim by fingerprint recognition is a commonplace
experience for millions of people in their daily life, e.g. for unlocking a
tablet computer or smartphone. The first processing step after fingerprint
image acquisition is segmentation, i.e. dividing a fingerprint image into a
foreground region whi... | 1505.04585 | http://arxiv.org/abs/1505.04585v1 | http://arxiv.org/pdf/1505.04585v1.pdf | [] | [] | [] |
56bYIWugI- | https://paperswithcode.com/paper/representing-multimodal-linguistic-annotated | Representing Multimodal Linguistic Annotated data | The question of interoperability for linguistic annotated resources covers different aspects. First, it requires a representation framework making it possible to compare, and eventually merge, different annotation schema. In this paper, a general description level representing the multimodal linguistic annotations is p... | null | https://www.aclweb.org/anthology/L14-1422/ | http://www.lrec-conf.org/proceedings/lrec2014/pdf/51_Paper.pdf | [] | [] | [] |
vmGwNe79OO | https://paperswithcode.com/paper/relations-on-fp-soft-sets-applied-to-decision | Relations on FP-Soft Sets Applied to Decision Making Problems | In this work, we first define relations on the fuzzy parametrized soft sets
and study their properties. We also give a decision making method based on
these relations. In approximate reasoning, relations on the fuzzy parametrized
soft sets have shown to be of a primordial importance. Finally, the method is
successfully... | 1402.3096 | http://arxiv.org/abs/1402.3096v1 | http://arxiv.org/pdf/1402.3096v1.pdf | [
"Decision Making"
] | [] | [] |
GAYlsIdpdS | https://paperswithcode.com/paper/tutorial-making-better-use-of-the-crowd | Tutorial: Making Better Use of the Crowd | Over the last decade, crowdsourcing has been used to harness the power of human computation to solve tasks that are notoriously difficult to solve with computers alone, such as determining whether or not an image contains a tree, rating the relevance of a website, or verifying the phone number of a business. The natura... | null | https://www.aclweb.org/anthology/P17-5006/ | https://www.aclweb.org/anthology/P17-5006 | [] | [] | [] |
GQVCqOf1OX | https://paperswithcode.com/paper/exploiting-the-value-of-the-center-dark | Exploiting the Value of the Center-dark Channel Prior for Salient Object Detection | Saliency detection aims to detect the most attractive objects in images and
is widely used as a foundation for various applications. In this paper, we
propose a novel salient object detection algorithm for RGB-D images using
center-dark channel priors. First, we generate an initial saliency map based on
a color salienc... | 1805.05132 | http://arxiv.org/abs/1805.05132v1 | http://arxiv.org/pdf/1805.05132v1.pdf | [
"Object Detection",
"RGB Salient Object Detection",
"Saliency Detection"
] | [] | [] |
LBbtv5WDiw | https://paperswithcode.com/paper/time-adaptive-reinforcement-learning | Time Adaptive Reinforcement Learning | Reinforcement learning (RL) allows to solve complex tasks such as Go often with a stronger performance than humans. However, the learned behaviors are usually fixed to specific tasks and unable to adapt to different contexts. Here we consider the case of adapting RL agents to different time restrictions, such as finish... | 2004.08600 | https://arxiv.org/abs/2004.08600v1 | https://arxiv.org/pdf/2004.08600v1.pdf | [] | [] | [] |
0w2Dl64Guc | https://paperswithcode.com/paper/content-based-image-retrieval-based-on-late | Content-Based Image Retrieval Based on Late Fusion of Binary and Local Descriptors | One of the challenges in Content-Based Image Retrieval (CBIR) is to reduce
the semantic gaps between low-level features and high-level semantic concepts.
In CBIR, the images are represented in the feature space and the performance of
CBIR depends on the type of selected feature representation. Late fusion also
known as... | 1703.08492 | http://arxiv.org/abs/1703.08492v1 | http://arxiv.org/pdf/1703.08492v1.pdf | [
"Content-Based Image Retrieval",
"Image Retrieval"
] | [] | [] |
CkChEzkhF0 | https://paperswithcode.com/paper/bioalbert-a-simple-and-effective-pre-trained | BioALBERT: A Simple and Effective Pre-trained Language Model for Biomedical Named Entity Recognition | In recent years, with the growing amount of biomedical documents, coupled with advancement in natural language processing algorithms, the research on biomedical named entity recognition (BioNER) has increased exponentially. However, BioNER research is challenging as NER in the biomedical domain are: (i) often restricte... | 2009.09223 | https://arxiv.org/abs/2009.09223v1 | https://arxiv.org/pdf/2009.09223v1.pdf | [
"Language Modelling",
"Named Entity Recognition"
] | [
"Adam",
"GELU",
"Dense Connections",
"Layer Normalization",
"WordPiece",
"Multi-Head Attention",
"LAMB",
"Scaled Dot-Product Attention",
"Residual Connection",
"Softmax",
"ALBERT"
] | [] |
k-tIbeJ4ct | https://paperswithcode.com/paper/amd-severity-prediction-and-explainability | AMD Severity Prediction And Explainability Using Image Registration And Deep Embedded Clustering | We propose a method to predict severity of age related macular degeneration (AMD) from input optical coherence tomography (OCT) images. Although there is no standard clinical severity scale for AMD, we leverage deep learning (DL) based image registration and clustering methods to identify diseased cases and predict the... | 1907.03075 | https://arxiv.org/abs/1907.03075v1 | https://arxiv.org/pdf/1907.03075v1.pdf | [
"Image Registration"
] | [] | [] |
prKUUVXhKd | https://paperswithcode.com/paper/rapid-online-analysis-of-local-feature | Rapid Online Analysis of Local Feature Detectors and Their Complementarity | A vision system that can assess its own performance and take appropriate
actions online to maximize its effectiveness would be a step towards achieving
the long-cherished goal of imitating humans. This paper proposes a method for
performing an online performance analysis of local feature detectors, the
primary stage of... | 1510.05145 | http://arxiv.org/abs/1510.05145v1 | http://arxiv.org/pdf/1510.05145v1.pdf | [
"Hypothesis Testing"
] | [] | [] |
JBAiPjMt7I | https://paperswithcode.com/paper/automated-model-selection-with-bayesian | Automated Model Selection with Bayesian Quadrature | We present a novel technique for tailoring Bayesian quadrature (BQ) to model
selection. The state-of-the-art for comparing the evidence of multiple models
relies on Monte Carlo methods, which converge slowly and are unreliable for
computationally expensive models. Previous research has shown that BQ offers
sample effic... | 1902.09724 | http://arxiv.org/abs/1902.09724v3 | http://arxiv.org/pdf/1902.09724v3.pdf | [
"Model Selection"
] | [] | [] |
RbcNs_t8T4 | https://paperswithcode.com/paper/recurrent-and-spiking-modeling-of-sparse | Recurrent and Spiking Modeling of Sparse Surgical Kinematics | Robot-assisted minimally invasive surgery is improving surgeon performance and patient outcomes. This innovation is also turning what has been a subjective practice into motion sequences that can be precisely measured. A growing number of studies have used machine learning to analyze video and kinematic data captured f... | 2005.05868 | https://arxiv.org/abs/2005.05868v2 | https://arxiv.org/pdf/2005.05868v2.pdf | [] | [] | [] |
BDgTX7eDt4 | https://paperswithcode.com/paper/reward-rational-implicit-choice-a-unifying | Reward-rational (implicit) choice: A unifying formalism for reward learning | It is often difficult to hand-specify what the correct reward function is for a task, so researchers have instead aimed to learn reward functions from human behavior or feedback. The types of behavior interpreted as evidence of the reward function have expanded greatly in recent years. We've gone from demonstrations, t... | 2002.04833 | https://arxiv.org/abs/2002.04833v3 | https://arxiv.org/pdf/2002.04833v3.pdf | [] | [] | [] |
6wsVeATLFw | https://paperswithcode.com/paper/improving-social-media-text-summarization-by | Improving Social Media Text Summarization by Learning Sentence Weight Distribution | Recently, encoder-decoder models are widely used in social media text
summarization. However, these models sometimes select noise words in irrelevant
sentences as part of a summary by error, thus declining the performance. In
order to inhibit irrelevant sentences and focus on key information, we propose
an effective ap... | 1710.11332 | http://arxiv.org/abs/1710.11332v1 | http://arxiv.org/pdf/1710.11332v1.pdf | [
"Text Summarization"
] | [] | [] |
KASonwd5a5 | https://paperswithcode.com/paper/an-industrial-case-study-on-shrinking-code | An Industrial Case Study on Shrinking Code Review Changesets through Remark Prediction | Change-based code review is used widely in industrial software development.
Thus, research on tools that help the reviewer to achieve better review
performance can have a high impact. We analyze one possibility to provide
cognitive support for the reviewer: Determining the importance of change parts
for review, specifi... | 1812.09510 | http://arxiv.org/abs/1812.09510v1 | http://arxiv.org/pdf/1812.09510v1.pdf | [] | [] | [] |
BnPqXRv_d5 | https://paperswithcode.com/paper/improving-sequence-to-sequence-learning-via | Improving Sequence-to-Sequence Learning via Optimal Transport | Sequence-to-sequence models are commonly trained via maximum likelihood
estimation (MLE). However, standard MLE training considers a word-level
objective, predicting the next word given the previous ground-truth partial
sentence. This procedure focuses on modeling local syntactic patterns, and may
fail to capture long-... | 1901.06283 | http://arxiv.org/abs/1901.06283v1 | http://arxiv.org/pdf/1901.06283v1.pdf | [
"Abstractive Text Summarization",
"Image Captioning",
"Machine Translation",
"Text Summarization"
] | [] | [] |
r-3xhWbO3c | https://paperswithcode.com/paper/on-the-tractability-of-minimal-model | On the Tractability of Minimal Model Computation for Some CNF Theories | Designing algorithms capable of efficiently constructing minimal models of
CNFs is an important task in AI. This paper provides new results along this
research line and presents new algorithms for performing minimal model finding
and checking over positive propositional CNFs and model minimization over
propositional CN... | 1310.8120 | http://arxiv.org/abs/1310.8120v1 | http://arxiv.org/pdf/1310.8120v1.pdf | [] | [] | [] |
6ddjquarg7 | https://paperswithcode.com/paper/two-step-joint-model-for-drug-drug | Two Step Joint Model for Drug Drug Interaction Extraction | When patients need to take medicine, particularly taking more than one kind of drug simultaneously, they should be alarmed that there possibly exists drug-drug interaction. Interaction between drugs may have a negative impact on patients or even cause death. Generally, drugs that conflict with a specific drug (or label... | 2008.12704 | https://arxiv.org/abs/2008.12704v1 | https://arxiv.org/pdf/2008.12704v1.pdf | [
"Drug–drug interaction extraction",
"Named Entity Recognition",
"Relation Extraction"
] | [] | [] |
f23tD4_KgB | https://paperswithcode.com/paper/adversarial-item-promotion-vulnerabilities-at | Adversarial Item Promotion: Vulnerabilities at the Core of Top-N Recommenders that Use Images to Address Cold Start | E-commerce platforms provide their customers with ranked lists of recommended items matching the customers' preferences. Merchants on e-commerce platforms would like their items to appear as high as possible in the top-N of these ranked lists. In this paper, we demonstrate how unscrupulous merchants can create item ima... | 2006.01888 | https://arxiv.org/abs/2006.01888v3 | https://arxiv.org/pdf/2006.01888v3.pdf | [
"Recommendation Systems"
] | [] | [] |
N2zKEm9Cdp | https://paperswithcode.com/paper/classification-of-quantitative-light-induced | Classification of Quantitative Light-Induced Fluorescence Images Using Convolutional Neural Network | Images are an important data source for diagnosis and treatment of oral
diseases. The manual classification of images may lead to misdiagnosis or
mistreatment due to subjective errors. In this paper an image classification
model based on Convolutional Neural Network is applied to Quantitative
Light-induced Fluorescence... | 1705.09193 | http://arxiv.org/abs/1705.09193v1 | http://arxiv.org/pdf/1705.09193v1.pdf | [
"Image Classification"
] | [] | [] |
BJcBusi3tp | https://paperswithcode.com/paper/uqam-ntl-named-entity-recognition-in-twitter | UQAM-NTL: Named entity recognition in Twitter messages | This paper describes our system used in the 2nd Workshop on Noisy User-generated Text (WNUT) shared task for Named Entity Recognition (NER) in Twitter, in conjunction with Coling 2016. Our system is based on supervised machine learning by applying Conditional Random Fields (CRF) to train two classifiers for two evaluat... | null | https://www.aclweb.org/anthology/W16-3926/ | https://www.aclweb.org/anthology/W16-3926 | [
"Language Modelling",
"Named Entity Recognition"
] | [] | [] |
YGtc7qEi9G | https://paperswithcode.com/paper/bilevel-continual-learning | Bilevel Continual Learning | Continual learning aims to learn continuously from a stream of tasks and data in an online-learning fashion, being capable of exploiting what was learned previously to improve current and future tasks while still being able to perform well on the previous tasks. One common limitation of many existing continual learning... | 2007.15553 | https://arxiv.org/abs/2007.15553v1 | https://arxiv.org/pdf/2007.15553v1.pdf | [
"bilevel optimization",
"Continual Learning",
"Transfer Learning"
] | [] | [] |
N-KMahja33 | https://paperswithcode.com/paper/table-to-text-describing-table-region-with | Table-to-Text: Describing Table Region with Natural Language | In this paper, we present a generative model to generate a natural language
sentence describing a table region, e.g., a row. The model maps a row from a
table to a continuous vector and then generates a natural language sentence by
leveraging the semantics of a table. To deal with rare words appearing in a
table, we de... | 1805.11234 | http://arxiv.org/abs/1805.11234v1 | http://arxiv.org/pdf/1805.11234v1.pdf | [
"Language Modelling"
] | [] | [] |
lqhD90uhjV | https://paperswithcode.com/paper/190910304 | Where to Look Next: Unsupervised Active Visual Exploration on 360° Input | We address the problem of active visual exploration of large 360{\deg} inputs. In our setting an active agent with a limited camera bandwidth explores its 360{\deg} environment by changing its viewing direction at limited discrete time steps. As such, it observes the world as a sequence of narrow field-of-view 'glimpse... | 1909.10304 | https://arxiv.org/abs/1909.10304v2 | https://arxiv.org/pdf/1909.10304v2.pdf | [] | [] | [] |
8FWasyUHdy | https://paperswithcode.com/paper/multi-view-constraint-propagation-with | Multi-View Constraint Propagation with Consensus Prior Knowledge | In many applications, the pairwise constraint is a kind of weaker supervisory
information which can be collected easily. The constraint propagation has been
proved to be a success of exploiting such side-information. In recent years,
some methods of multi-view constraint propagation have been proposed. However,
the pro... | 1609.06456 | http://arxiv.org/abs/1609.06456v1 | http://arxiv.org/pdf/1609.06456v1.pdf | [] | [] | [] |
1WUiuyCy5J | https://paperswithcode.com/paper/triad-state-space-construction-for-chaotic | Triad State Space Construction for Chaotic Signal Classification with Deep Learning | Inspired by the well-known permutation entropy (PE), an effective image encoding scheme for chaotic time series, Triad State Space Construction (TSSC), is proposed. The TSSC image can recognize higher-order temporal patterns and identify new forbidden regions in time series motifs beyond the Bandt-Pompe probabilities. ... | 2003.11931 | https://arxiv.org/abs/2003.11931v1 | https://arxiv.org/pdf/2003.11931v1.pdf | [
"Image Classification",
"Time Series"
] | [] | [] |
dKPpkj0mb7 | https://paperswithcode.com/paper/differentially-private-assouad-fano-and-le | Differentially Private Assouad, Fano, and Le Cam | Le Cam's method, Fano's inequality, and Assouad's lemma are three widely used techniques to prove lower bounds for statistical estimation tasks. We propose their analogues under central differential privacy. Our results are simple, easy to apply and we use them to establish sample complexity bounds in several estimatio... | 2004.06830 | https://arxiv.org/abs/2004.06830v2 | https://arxiv.org/pdf/2004.06830v2.pdf | [] | [] | [] |
WN2RbXMGNz | https://paperswithcode.com/paper/temporal-graph-kernels-for-classifying | Temporal Graph Kernels for Classifying Dissemination Processes | Many real-world graphs or networks are temporal, e.g., in a social network persons only interact at specific points in time. This information directs dissemination processes on the network, such as the spread of rumors, fake news, or diseases. However, the current state-of-the-art methods for supervised graph classific... | 1911.05496 | https://arxiv.org/abs/1911.05496v1 | https://arxiv.org/pdf/1911.05496v1.pdf | [
"Graph Classification"
] | [] | [] |
OJRVkVT6ZA | https://paperswithcode.com/paper/stream-packing-for-asynchronous-multi-context | Stream Packing for Asynchronous Multi-Context Systems using ASP | When a processing unit relies on data from external streams, we may face the
problem that the stream data needs to be rearranged in a way that allows the
unit to perform its task(s). On arrival of new data, we must decide whether
there is sufficient information available to start processing or whether to
wait for more ... | 1611.05640 | http://arxiv.org/abs/1611.05640v1 | http://arxiv.org/pdf/1611.05640v1.pdf | [] | [] | [] |
UB037upbpb | https://paperswithcode.com/paper/resolvable-designs-for-speeding-up | Resolvable Designs for Speeding up Distributed Computing | Distributed computing frameworks such as MapReduce are often used to process large computational jobs. They operate by partitioning each job into smaller tasks executed on different servers. The servers also need to exchange intermediate values to complete the computation. Experimental evidence suggests that this so-ca... | 1908.05666 | https://arxiv.org/abs/1908.05666v3 | https://arxiv.org/pdf/1908.05666v3.pdf | [
"Distributed Computing"
] | [] | [] |
V6ABnNWwVx | https://paperswithcode.com/paper/image-co-localization-by-mimicking-a-good | Image Co-localization by Mimicking a Good Detector's Confidence Score Distribution | Given a set of images containing objects from the same category, the task of
image co-localization is to identify and localize each instance. This paper
shows that this problem can be solved by a simple but intriguing idea, that is,
a common object detector can be learnt by making its detection confidence
scores distri... | 1603.04619 | http://arxiv.org/abs/1603.04619v2 | http://arxiv.org/pdf/1603.04619v2.pdf | [] | [] | [] |
ww4Lw_RhGg | https://paperswithcode.com/paper/detecting-british-columbia-coastal-rainfall | Detecting British Columbia Coastal Rainfall Patterns by Clustering Gaussian Processes | Functional data analysis is a statistical framework where data are assumed to follow some functional form. This method of analysis is commonly applied to time series data, where time, measured continuously or in discrete intervals, serves as the location for a function's value. Gaussian processes are a generalization o... | 1812.09758 | https://arxiv.org/abs/1812.09758v2 | https://arxiv.org/pdf/1812.09758v2.pdf | [
"Gaussian Processes",
"Time Series"
] | [] | [] |
_T4316_adn | https://paperswithcode.com/paper/bilinear-parameterization-for-differentiable | Bilinear Parameterization For Differentiable Rank-Regularization | Low rank approximation is a commonly occurring problem in many computer vision and machine learning applications. There are two common ways of optimizing the resulting models. Either the set of matrices with a given rank can be explicitly parametrized using a bilinear factorization, or low rank can be implicitly enforc... | 1811.11088 | https://arxiv.org/abs/1811.11088v3 | https://arxiv.org/pdf/1811.11088v3.pdf | [] | [] | [] |
mGr5uVktUs | https://paperswithcode.com/paper/perturbed-masking-parameter-free-probing-for | Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT | By introducing a small set of additional parameters, a probe learns to solve specific linguistic tasks (e.g., dependency parsing) in a supervised manner using feature representations (e.g., contextualized embeddings). The effectiveness of such probing tasks is taken as evidence that the pre-trained model encodes lingui... | 2004.14786 | https://arxiv.org/abs/2004.14786v2 | https://arxiv.org/pdf/2004.14786v2.pdf | [
"Dependency Parsing",
"Language Modelling",
"Sentiment Analysis"
] | [
"Residual Connection",
"Attention Dropout",
"Linear Warmup With Linear Decay",
"Weight Decay",
"GELU",
"Dense Connections",
"Adam",
"WordPiece",
"Softmax",
"Dropout",
"Multi-Head Attention",
"Layer Normalization",
"Scaled Dot-Product Attention",
"BERT"
] | [] |
h5TnCNH_MZ | https://paperswithcode.com/paper/uaic-at-semeval-2019-task-3-extracting-much | UAIC at SemEval-2019 Task 3: Extracting Much from Little | In this paper, we present a system description for implementing a sentiment analysis agent capable of interpreting the state of an interlocutor engaged in short three message conversations. We present the results and observations of our work and which parts could be further improved in the future. | null | https://www.aclweb.org/anthology/S19-2062/ | https://www.aclweb.org/anthology/S19-2062 | [
"Sentiment Analysis"
] | [] | [] |
v4S2mjOaG7 | https://paperswithcode.com/paper/automated-quantification-of-ct-patterns | Machine Learning Automatically Detects COVID-19 using Chest CTs in a Large Multicenter Cohort | Objectives: To investigate machine-learning classifiers and interpretable models using chest CT for detection of COVID-19 and differentiation from other pneumonias, ILD and normal CTs. Methods: Our retrospective multi-institutional study obtained 2096 chest CTs from 16 institutions (including 1077 COVID-19 patients). T... | 2006.04998 | https://arxiv.org/abs/2006.04998v3 | https://arxiv.org/pdf/2006.04998v3.pdf | [] | [
"Logistic Regression"
] | [] |
3jfxctTGse | https://paperswithcode.com/paper/deepasl-kinetic-model-incorporated-loss-for | DeepASL: Kinetic Model Incorporated Loss for Denoising Arterial Spin Labeled MRI via Deep Residual Learning | Arterial spin labeling (ASL) allows to quantify the cerebral blood flow (CBF)
by magnetic labeling of the arterial blood water. ASL is increasingly used in
clinical studies due to its noninvasiveness, repeatability and benefits in
quantification. However, ASL suffers from an inherently low-signal-to-noise
ratio (SNR) r... | 1804.02755 | http://arxiv.org/abs/1804.02755v2 | http://arxiv.org/pdf/1804.02755v2.pdf | [
"Denoising"
] | [] | [] |
lUrE3YPVVU | https://paperswithcode.com/paper/slot-gated-modeling-for-joint-slot-filling | Slot-Gated Modeling for Joint Slot Filling and Intent Prediction | Attention-based recurrent neural network models for joint intent detection and slot filling have achieved the state-of-the-art performance, while they have independent attention weights. Considering that slot and intent have the strong relationship, this paper proposes a slot gate that focuses on learning the relations... | null | https://www.aclweb.org/anthology/N18-2118/ | https://www.aclweb.org/anthology/N18-2118 | [
"Intent Detection",
"Slot Filling",
"Spoken Dialogue Systems",
"Spoken Language Understanding"
] | [] | [] |
G4JSyhn_Kj | https://paperswithcode.com/paper/tag-embedding-based-personalized-point-of | Tag Embedding Based Personalized Point Of Interest Recommendation System | Personalized Point of Interest recommendation is very helpful for satisfying users' needs at new places. In this article, we propose a tag embedding based method for Personalized Recommendation of Point Of Interest. We model the relationship between tags corresponding to Point Of Interest. The model provides representa... | 2004.06389 | https://arxiv.org/abs/2004.06389v1 | https://arxiv.org/pdf/2004.06389v1.pdf | [] | [] | [] |
Y15jNn_RvU | https://paperswithcode.com/paper/a-self-correcting-deep-learning-approach-to | A Self-Correcting Deep Learning Approach to Predict Acute Conditions in Critical Care | In critical care, intensivists are required to continuously monitor high
dimensional vital signs and lab measurements to detect and diagnose acute
patient conditions. This has always been a challenging task. In this study, we
propose a novel self-correcting deep learning prediction approach to address
this challenge. W... | 1901.04364 | http://arxiv.org/abs/1901.04364v1 | http://arxiv.org/pdf/1901.04364v1.pdf | [] | [] | [] |
b6IQ6mXVu3 | https://paperswithcode.com/paper/textimager-a-distributed-uima-based-system | TextImager: a Distributed UIMA-based System for NLP | More and more disciplines require NLP tools for performing automatic text analyses on various levels of linguistic resolution. However, the usage of established NLP frameworks is often hampered for several reasons: in most cases, they require basic to sophisticated programming skills, interfere with interoperability du... | null | https://www.aclweb.org/anthology/C16-2013/ | https://www.aclweb.org/anthology/C16-2013 | [
"Sentiment Analysis",
"Text Classification"
] | [] | [] |
_NOY3y3RmY | https://paperswithcode.com/paper/a-manually-annotated-chinese-corpus-for-non | A Manually Annotated Chinese Corpus for Non-task-oriented Dialogue Systems | This paper presents a large-scale corpus for non-task-oriented dialogue
response selection, which contains over 27K distinct prompts more than 82K
responses collected from social media. To annotate this corpus, we define a
5-grade rating scheme: bad, mediocre, acceptable, good, and excellent,
according to the relevance... | 1805.05542 | http://arxiv.org/abs/1805.05542v1 | http://arxiv.org/pdf/1805.05542v1.pdf | [
"Task-Oriented Dialogue Systems"
] | [] | [] |
40xyrLzaOA | https://paperswithcode.com/paper/radial-velocity-retrieval-for-multichannel | Radial Velocity Retrieval for Multichannel SAR Moving Targets with Time-Space Doppler De-ambiguity | In this paper, with respect to multichannel synthetic aperture radars (SAR),
we first formulate the problems of Doppler ambiguities on the radial velocity
(RV) estimation of a ground moving target in range-compressed domain,
range-Doppler domain and image domain, respectively. It is revealed that in
these problems, a c... | 1610.00070 | http://arxiv.org/abs/1610.00070v3 | http://arxiv.org/pdf/1610.00070v3.pdf | [] | [] | [] |
sbfpN12Pnn | https://paperswithcode.com/paper/a-game-theoretic-analysis-of-additive | A Game Theoretic Analysis of Additive Adversarial Attacks and Defenses | Research in adversarial learning follows a cat and mouse game between attackers and defenders where attacks are proposed, they are mitigated by new defenses, and subsequently new attacks are proposed that break earlier defenses, and so on. However, it has remained unclear as to whether there are conditions under which ... | 2009.06530 | https://arxiv.org/abs/2009.06530v1 | https://arxiv.org/pdf/2009.06530v1.pdf | [] | [] | [] |
Tjnly3wdX9 | https://paperswithcode.com/paper/a-fundamental-performance-limitation-for | A Fundamental Performance Limitation for Adversarial Classification | Despite the widespread use of machine learning algorithms to solve problems
of technological, economic, and social relevance, provable guarantees on the
performance of these data-driven algorithms are critically lacking, especially
when the data originates from unreliable sources and is transmitted over
unprotected and... | 1903.01032 | http://arxiv.org/abs/1903.01032v2 | http://arxiv.org/pdf/1903.01032v2.pdf | [] | [] | [] |
GAuRj0APhm | https://paperswithcode.com/paper/undecidability-of-the-lambek-calculus-with | Undecidability of the Lambek calculus with subexponential and bracket modalities | The Lambek calculus is a well-known logical formalism for modelling natural
language syntax. The original calculus covered a substantial number of
intricate natural language phenomena, but only those restricted to the
context-free setting. In order to address more subtle linguistic issues, the
Lambek calculus has been ... | 1608.04020 | http://arxiv.org/abs/1608.04020v2 | http://arxiv.org/pdf/1608.04020v2.pdf | [] | [] | [] |
n1Qtgt39t6 | https://paperswithcode.com/paper/a-parameterized-family-of-meta-submodular | A Parameterized Family of Meta-Submodular Functions | Submodular function maximization has found a wealth of new applications in machine learning models during the past years. The related supermodular maximization models (submodular minimization) also offer an abundance of applications, but they appeared to be highly intractable even under simple cardinality constraints. ... | 2006.13754 | https://arxiv.org/abs/2006.13754v1 | https://arxiv.org/pdf/2006.13754v1.pdf | [] | [] | [] |
MOJEVoXTpV | https://paperswithcode.com/paper/attention-based-recurrent-neural-network | Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling | Attention-based encoder-decoder neural network models have recently shown
promising results in machine translation and speech recognition. In this work,
we propose an attention-based neural network model for joint intent detection
and slot filling, both of which are critical steps for many speech
understanding and dial... | 1609.01454 | http://arxiv.org/abs/1609.01454v1 | http://arxiv.org/pdf/1609.01454v1.pdf | [
"Intent Classification",
"Intent Detection",
"Slot Filling"
] | [] | [] |
pUvqW1_u-- | https://paperswithcode.com/paper/statistical-optimal-transport-via-factored | Statistical Optimal Transport via Factored Couplings | We propose a new method to estimate Wasserstein distances and optimal
transport plans between two probability distributions from samples in high
dimension. Unlike plug-in rules that simply replace the true distributions by
their empirical counterparts, our method promotes couplings with low transport
rank, a new struct... | 1806.07348 | http://arxiv.org/abs/1806.07348v3 | http://arxiv.org/pdf/1806.07348v3.pdf | [
"Domain Adaptation"
] | [] | [] |
wt9AF-3so5 | https://paperswithcode.com/paper/election-coding-for-distributed-learning | Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks | Recent advances in large-scale distributed learning algorithms have enabled communication-efficient training via SignSGD. Unfortunately, a major issue continues to plague distributed learning: namely, Byzantine failures may incur serious degradation in learning accuracy. This paper proposes Election Coding, a coding-th... | 1910.06093 | https://arxiv.org/abs/1910.06093v3 | https://arxiv.org/pdf/1910.06093v3.pdf | [] | [] | [] |
5gY4KMYJWN | https://paperswithcode.com/paper/a-hybrid-monte-carlo-ant-colony-optimization | A Hybrid Monte Carlo Ant Colony Optimization Approach for Protein Structure Prediction in the HP Model | The hydrophobic-polar (HP) model has been widely studied in the field of
protein structure prediction (PSP) both for theoretical purposes and as a
benchmark for new optimization strategies. In this work we introduce a new
heuristics based on Ant Colony Optimization (ACO) and Markov Chain Monte Carlo
(MCMC) that we call... | 1309.7690 | http://arxiv.org/abs/1309.7690v1 | http://arxiv.org/pdf/1309.7690v1.pdf | [] | [] | [] |
tCRttuVV0Z | https://paperswithcode.com/paper/multi-resolution-data-fusion-for-super | Multi-resolution Data Fusion for Super-Resolution Electron Microscopy | Perhaps surprisingly, the total electron microscopy (EM) data collected to
date is less than a cubic millimeter. Consequently, there is an enormous demand
in the materials and biological sciences to image at greater speed and lower
dosage, while maintaining resolution. Traditional EM imaging based on
homogeneous raster... | 1612.00874 | http://arxiv.org/abs/1612.00874v1 | http://arxiv.org/pdf/1612.00874v1.pdf | [
"Electron Microscopy",
"Super Resolution",
"Super-Resolution"
] | [] | [] |
FHQv8SZ8vk | https://paperswithcode.com/paper/a-comparison-of-information-retrieval | A Comparison of Information Retrieval Techniques for Detecting Source Code Plagiarism | Plagiarism is a commonly encountered problem in the academia. While there are
several tools and techniques to efficiently determine plagiarism in text, the
same cannot be said about source code plagiarism. To make the existing systems
more efficient, we use several information retrieval techniques to find the
similarit... | 1902.02407 | http://arxiv.org/abs/1902.02407v1 | http://arxiv.org/pdf/1902.02407v1.pdf | [
"Information Retrieval"
] | [] | [] |
_HxQfmrHbr | https://paperswithcode.com/paper/machine-learning-driven-synthesis-of-few | Machine learning driven synthesis of few-layered WTe2 | Reducing the lateral scale of two-dimensional (2D) materials to one-dimensional (1D) has attracted substantial research interest not only to achieve competitive electronic device applications but also for the exploration of fundamental physical properties. Controllable synthesis of high-quality 1D nanoribbons (NRs) is ... | 1910.04603 | https://arxiv.org/abs/1910.04603v1 | https://arxiv.org/pdf/1910.04603v1.pdf | [] | [] | [] |
s45-fsjOWp | https://paperswithcode.com/paper/a-survey-on-domain-adaptation-theory | A survey on domain adaptation theory: learning bounds and theoretical guarantees | All famous machine learning algorithms that comprise both supervised and semi-supervised learning work well only under a common assumption: the training and test data follow the same distribution. When the distribution changes, most statistical models must be reconstructed from newly collected data, which for some appl... | 2004.11829 | https://arxiv.org/abs/2004.11829v5 | https://arxiv.org/pdf/2004.11829v5.pdf | [
"Domain Adaptation",
"Transfer Learning"
] | [] | [] |
Iyt0SaCfxE | https://paperswithcode.com/paper/geometric-learning-and-topological-inference | Geometric Learning and Topological Inference with Biobotic Networks: Convergence Analysis | In this study, we present and analyze a framework for geometric and
topological estimation for mapping of unknown environments. We consider agents
mimicking motion behaviors of cyborg insects, known as biobots, and exploit
coordinate-free local interactions among them to infer geometric and
topological information abou... | 1607.00051 | http://arxiv.org/abs/1607.00051v1 | http://arxiv.org/pdf/1607.00051v1.pdf | [
"Topological Data Analysis"
] | [] | [] |
ht6haRsvVR | https://paperswithcode.com/paper/a-parallel-memory-efficient-epistemic-logic | A Parallel Memory-efficient Epistemic Logic Program Solver: Harder, Better, Faster | As the practical use of answer set programming (ASP) has grown with the
development of efficient solvers, we expect a growing interest in extensions of
ASP as their semantics stabilize and solvers supporting them mature. Epistemic
Specifications, which adds modal operators K and M to the language of ASP, is
one such ex... | 1608.06910 | http://arxiv.org/abs/1608.06910v2 | http://arxiv.org/pdf/1608.06910v2.pdf | [] | [] | [] |
H5szLqaUFs | https://paperswithcode.com/paper/distributed-learning-with-infinitely-many | Distributed Learning with Infinitely Many Hypotheses | We consider a distributed learning setup where a network of agents
sequentially access realizations of a set of random variables with unknown
distributions. The network objective is to find a parametrized distribution
that best describes their joint observations in the sense of the
Kullback-Leibler divergence. Apart fr... | 1605.02105 | http://arxiv.org/abs/1605.02105v1 | http://arxiv.org/pdf/1605.02105v1.pdf | [] | [] | [] |
Cd2-Fo5XYm | https://paperswithcode.com/paper/outlier-guided-optimization-of-abdominal | Outlier Guided Optimization of Abdominal Segmentation | Abdominal multi-organ segmentation of computed tomography (CT) images has been the subject of extensive research interest. It presents a substantial challenge in medical image processing, as the shape and distribution of abdominal organs can vary greatly among the population and within an individual over time. While co... | 2002.04098 | https://arxiv.org/abs/2002.04098v1 | https://arxiv.org/pdf/2002.04098v1.pdf | [
"Active Learning",
"Computed Tomography (CT)"
] | [
"Concatenated Skip Connection",
"ReLU",
"Max Pooling",
"Convolution",
"U-Net"
] | [] |
eWcDFq_N-B | https://paperswithcode.com/paper/automatic-generation-of-algorithms-for-black | Automatic Generation of Algorithms for Black-Box Robust Optimisation Problems | We develop algorithms capable of tackling robust black-box optimisation problems, where the number of model runs is limited. When a desired solution cannot be implemented exactly the aim is to find a robust one, where the worst case in an uncertainty neighbourhood around a solution still performs well. This requires a ... | 2004.07294 | https://arxiv.org/abs/2004.07294v1 | https://arxiv.org/pdf/2004.07294v1.pdf | [] | [] | [] |
W1RaStCQMx | https://paperswithcode.com/paper/semantic-discord-finding-unusual-local | Semantic Discord: Finding Unusual Local Patterns for Time Series | Finding anomalous subsequence in a long time series is a very important but difficult problem. Existing state-of-the-art methods have been focusing on searching for the subsequence that is the most dissimilar to the rest of the subsequences; however, they do not take into account the background patterns that contain th... | 2001.11842 | https://arxiv.org/abs/2001.11842v2 | https://arxiv.org/pdf/2001.11842v2.pdf | [
"Time Series"
] | [] | [] |
8lQDYvNCD9 | https://paperswithcode.com/paper/sockpuppet-detection-in-wikipedia-a-corpus-of | Sockpuppet Detection in Wikipedia: A Corpus of Real-World Deceptive Writing for Linking Identities | This paper describes the corpus of sockpuppet cases we gathered from
Wikipedia. A sockpuppet is an online user account created with a fake identity
for the purpose of covering abusive behavior and/or subverting the editing
regulation process. We used a semi-automated method for crawling and curating a
dataset of real s... | 1310.6772 | http://arxiv.org/abs/1310.6772v1 | http://arxiv.org/pdf/1310.6772v1.pdf | [] | [] | [] |
5N_8UtE2ez | https://paperswithcode.com/paper/on-dropout-overfitting-and-interaction | On Dropout, Overfitting, and Interaction Effects in Deep Neural Networks | We examine Dropout through the perspective of interactions: learned effects that combine multiple input variables. Given $N$ variables, there are $O(N^2)$ possible pairwise interactions, $O(N^3)$ possible 3-way interactions, etc. We show that Dropout implicitly sets a learning rate for interaction effects that decays e... | 2007.00823 | https://arxiv.org/abs/2007.00823v1 | https://arxiv.org/pdf/2007.00823v1.pdf | [] | [
"Weight Decay",
"Early Stopping",
"Dropout"
] | [] |
7kubH1Mo3K | https://paperswithcode.com/paper/dream-a-challenge-data-set-and-models-for | DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension | We present DREAM, the first dialogue-based multiple-choice reading comprehension data set. Collected from English as a Foreign Language examinations designed by human experts to evaluate the comprehension level of Chinese learners of English, our data set contains 10,197 multiple-choice questions for 6,444 dialogues. I... | null | https://www.aclweb.org/anthology/Q19-1014/ | https://www.aclweb.org/anthology/Q19-1014 | [
"Dialogue Understanding",
"Reading Comprehension"
] | [] | [] |
rgVg36W7TV | https://paperswithcode.com/paper/heavy-hitters-via-cluster-preserving | Heavy hitters via cluster-preserving clustering | In turnstile $\ell_p$ $\varepsilon$-heavy hitters, one maintains a
high-dimensional $x\in\mathbb{R}^n$ subject to $\texttt{update}(i,\Delta)$
causing $x_i\leftarrow x_i + \Delta$, where $i\in[n]$, $\Delta\in\mathbb{R}$.
Upon receiving a query, the goal is to report a small list $L\subset[n]$, $|L|
= O(1/\varepsilon^p)$... | 1604.01357 | http://arxiv.org/abs/1604.01357v1 | http://arxiv.org/pdf/1604.01357v1.pdf | [] | [] | [] |
4JJvCfz61Q | https://paperswithcode.com/paper/what-does-it-mean-to-solve-the-problem-of | What does it mean to solve the problem of discrimination in hiring? Social, technical and legal perspectives from the UK on automated hiring systems | The ability to get and keep a job is a key aspect of participating in society and sustaining livelihoods. Yet the way decisions are made on who is eligible for jobs, and why, are rapidly changing with the advent and growth in uptake of automated hiring systems (AHSs) powered by data-driven tools. Key concerns about suc... | 1910.06144 | https://arxiv.org/abs/1910.06144v2 | https://arxiv.org/pdf/1910.06144v2.pdf | [] | [] | [] |
TwP82tP1B2 | https://paperswithcode.com/paper/hierarchical-modeling-and-shrinkage-for-user | Hierarchical Modeling and Shrinkage for User Session Length Prediction in Media Streaming | An important metric of users' satisfaction and engagement within on-line
streaming services is the user session length, i.e. the amount of time they
spend on a service continuously without interruption. Being able to predict
this value directly benefits the recommendation and ad pacing contexts in music
and video strea... | 1803.01440 | http://arxiv.org/abs/1803.01440v2 | http://arxiv.org/pdf/1803.01440v2.pdf | [] | [] | [] |
0mFlytoqDq | https://paperswithcode.com/paper/discrete-potts-model-for-generating | Discrete Potts Model for Generating Superpixels on Noisy Images | Many computer vision applications, such as object recognition and
segmentation, increasingly build on superpixels. However, there have been so
far few superpixel algorithms that systematically deal with noisy images. We
propose to first decompose the image into equal-sized rectangular patches,
which also sets the maxim... | 1803.07351 | http://arxiv.org/abs/1803.07351v1 | http://arxiv.org/pdf/1803.07351v1.pdf | [
"Denoising",
"Object Recognition"
] | [] | [] |
GwH-pi0pKA | https://paperswithcode.com/paper/a-path-towards-quantum-advantage-in-training | A Path Towards Quantum Advantage in Training Deep Generative Models with Quantum Annealers | The development of quantum-classical hybrid (QCH) algorithms is critical to achieve state-of-the-art computational models. A QCH variational autoencoder (QVAE) was introduced in Ref. [1] by some of the authors of this paper. QVAE consists of a classical auto-encoding structure realized by traditional deep neural networ... | 1912.02119 | https://arxiv.org/abs/1912.02119v1 | https://arxiv.org/pdf/1912.02119v1.pdf | [] | [
"AutoEncoder"
] | [] |
-KDZXl-Grv | https://paperswithcode.com/paper/hhu-at-semeval-2019-task-6-context-does | HHU at SemEval-2019 Task 6: Context Does Matter - Tackling Offensive Language Identification and Categorization with ELMo | We present our results for OffensEval: Identifying and Categorizing Offensive Language in Social Media (SemEval 2019 - Task 6). Our results show that context embeddings are important features for the three different sub-tasks in connection with classical machine and with deep learning. Our best model reached place 3 of... | null | https://www.aclweb.org/anthology/S19-2112/ | https://www.aclweb.org/anthology/S19-2112 | [
"Language Identification"
] | [] | [] |
b35rdg_Mv6 | https://paperswithcode.com/paper/sold-sub-optimal-low-rank-decomposition-for | SOLD: Sub-Optimal Low-rank Decomposition for Efficient Video Segmentation | This paper investigates how to perform robust and efficient unsupervised video segmentation while suppressing the effects of data noises and/or corruptions. We propose a general algorithm, called Sub-Optimal Low-rank Decomposition (SOLD), which pursues the low-rank representation for video segmentation. Given the super... | null | http://openaccess.thecvf.com/content_cvpr_2015/html/Li_SOLD_Sub-Optimal_Low-rank_2015_CVPR_paper.html | http://openaccess.thecvf.com/content_cvpr_2015/papers/Li_SOLD_Sub-Optimal_Low-rank_2015_CVPR_paper.pdf | [
"Video Segmentation",
"Video Semantic Segmentation"
] | [] | [] |
BUr1ldXfAZ | https://paperswithcode.com/paper/a-survey-of-end-to-end-driving-architectures | A Survey of End-to-End Driving: Architectures and Training Methods | Autonomous driving is of great interest to industry and academia alike. The use of machine learning approaches for autonomous driving has long been studied, but mostly in the context of perception. In this paper we take a deeper look on the so called end-to-end approaches for autonomous driving, where the entire drivin... | 2003.06404 | https://arxiv.org/abs/2003.06404v1 | https://arxiv.org/pdf/2003.06404v1.pdf | [
"Autonomous Driving"
] | [] | [] |
zKqd-edmpG | https://paperswithcode.com/paper/modeling-nanoconfinement-effects-using-active | Modeling nanoconfinement effects using active learning | Predicting the spatial configuration of gas molecules in nanopores of shale formations is crucial for fluid flow forecasting and hydrocarbon reserves estimation. The key challenge in these tight formations is that the majority of the pore sizes are less than 50 nm. At this scale, the fluid properties are affected by na... | 2005.02587 | https://arxiv.org/abs/2005.02587v2 | https://arxiv.org/pdf/2005.02587v2.pdf | [
"Active Learning"
] | [] | [] |
YMy8y6ZCpB | https://paperswithcode.com/paper/deepiso-a-deep-learning-model-for-peptide | DeepIso: A Deep Learning Model for Peptide Feature Detection | Liquid chromatography with tandem mass spectrometry (LC-MS/MS) based
proteomics is a well-established research field with major applications such as
identification of disease biomarkers, drug discovery, drug design and
development. In proteomics, protein identification and quantification is a
fundamental task, which is... | 1801.01539 | http://arxiv.org/abs/1801.01539v1 | http://arxiv.org/pdf/1801.01539v1.pdf | [
"Drug Discovery"
] | [] | [] |
MpQXSSQuDw | https://paperswithcode.com/paper/evidence-based-explanation-to-promote | Evidence-based explanation to promote fairness in AI systems | As Artificial Intelligence (AI) technology gets more intertwined with every system, people are using AI to make decisions on their everyday activities. In simple contexts, such as Netflix recommendations, or in more complex context like in judicial scenarios, AI is part of people's decisions. People make decisions and ... | 2003.01525 | https://arxiv.org/abs/2003.01525v1 | https://arxiv.org/pdf/2003.01525v1.pdf | [
"Decision Making",
"fairness"
] | [] | [] |
N8ciErVgPB | https://paperswithcode.com/paper/change-your-singer-a-transfer-learning | Change your singer: a transfer learning generative adversarial framework for song to song conversion | Have you ever wondered how a song might sound if performed by a different artist? In this work, we propose SCM-GAN, an end-to-end non-parallel song conversion system powered by generative adversarial and transfer learning that allows users to listen to a selected target singer singing any song. SCM-GAN first separates ... | 1911.02933 | https://arxiv.org/abs/1911.02933v2 | https://arxiv.org/pdf/1911.02933v2.pdf | [
"Transfer Learning",
"Voice Conversion"
] | [
"Concatenated Skip Connection",
"ReLU",
"Max Pooling",
"Convolution",
"U-Net"
] | [] |
ykpBfsdFld | https://paperswithcode.com/paper/transforming-spectrum-and-prosody-for | Transforming Spectrum and Prosody for Emotional Voice Conversion with Non-Parallel Training Data | Emotional voice conversion aims to convert the spectrum and prosody to change the emotional patterns of speech, while preserving the speaker identity and linguistic content. Many studies require parallel speech data between different emotional patterns, which is not practical in real life. Moreover, they often model th... | 2002.00198 | https://arxiv.org/abs/2002.00198v4 | https://arxiv.org/pdf/2002.00198v4.pdf | [
"Voice Conversion"
] | [
"Batch Normalization",
"Residual Connection",
"PatchGAN",
"ReLU",
"Tanh Activation",
"Residual Block",
"Instance Normalization",
"Convolution",
"Leaky ReLU",
"Sigmoid Activation",
"GAN Least Squares Loss",
"Cycle Consistency Loss",
"CycleGAN"
] | [] |
c98LHxRuC9 | https://paperswithcode.com/paper/droidstar-callback-typestates-for-android | DroidStar: Callback Typestates for Android Classes | Event-driven programming frameworks, such as Android, are based on components
with asynchronous interfaces. The protocols for interacting with these
components can often be described by finite-state machines we dub *callback
typestates*. Callback typestates are akin to classical typestates, with the
difference that the... | 1701.07842 | http://arxiv.org/abs/1701.07842v3 | http://arxiv.org/pdf/1701.07842v3.pdf | [
"Active Learning"
] | [] | [] |
0rDgd-odj- | https://paperswithcode.com/paper/empirical-risk-minimization-is-consistent | Empirical risk minimization is consistent with the mean absolute percentage error | We study in this paper the consequences of using the Mean Absolute Percentage
Error (MAPE) as a measure of quality for regression models. We show that
finding the best model under the MAPE is equivalent to doing weighted Mean
Absolute Error (MAE) regression. We also show that, under some asumptions,
universal consisten... | 1509.02357 | http://arxiv.org/abs/1509.02357v1 | http://arxiv.org/pdf/1509.02357v1.pdf | [] | [] | [] |
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