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Title: Intelligent location of simultaneously active acoustic emission sources: Part I |
Abstract: The intelligent acoustic emission locator is described in Part I, while Part II discusses blind source separation, time delay estimation and location of two simultaneously active continuous acoustic emission sources. The location of acoustic emission on complicated aircraft frame structures is a difficult pro... |
Title: Intelligent location of simultaneously active acoustic emission sources: Part II |
Abstract: Part I describes an intelligent acoustic emission locator, while Part II discusses blind source separation, time delay estimation and location of two continuous acoustic emission sources. Acoustic emission (AE) analysis is used for characterization and location of developing defects in materials. AE sources o... |
Title: The World as Evolving Information |
Abstract: This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical... |
Title: Learning from compressed observations |
Abstract: The problem of statistical learning is to construct a predictor of a random variable $Y$ as a function of a related random variable $X$ on the basis of an i.i.d. training sample from the joint distribution of $(X,Y)$. Allowable predictors are drawn from some specified class, and the goal is to approach asympt... |
Title: Computation of Power Loss in Likelihood Ratio Tests for Probability Densities Extended by Lehmann Alternatives |
Abstract: We compute the loss of power in likelihood ratio tests when we test the original parameter of a probability density extended by the first Lehmann alternative. |
Title: Quantifying social group evolution |
Abstract: The rich set of interactions between individuals in the society results in complex community structure, capturing highly connected circles of friends, families, or professional cliques in a social network. Thanks to frequent changes in the activity and communication patterns of individuals, the associated soc... |
Title: Metropolis algorithm and equienergy sampling for two mean field spin systems |
Abstract: In this paper we study the Metropolis algorithm in connection with two mean--field spin systems, the so called mean--field Ising model and the Blume--Emery--Griffiths model. In both this examples the naive choice of proposal chain gives rise, for some parameters, to a slowly mixing Metropolis chain, that is a... |
Title: Sensor Networks with Random Links: Topology Design for Distributed Consensus |
Abstract: In a sensor network, in practice, the communication among sensors is subject to:(1) errors or failures at random times; (3) costs; and(2) constraints since sensors and networks operate under scarce resources, such as power, data rate, or communication. The signal-to-noise ratio (SNR) is usually a main factor ... |
Title: Architecture for Pseudo Acausal Evolvable Embedded Systems |
Abstract: Advances in semiconductor technology are contributing to the increasing complexity in the design of embedded systems. Architectures with novel techniques such as evolvable nature and autonomous behavior have engrossed lot of attention. This paper demonstrates conceptually evolvable embedded systems can be cha... |
Title: The on-line shortest path problem under partial monitoring |
Abstract: The on-line shortest path problem is considered under various models of partial monitoring. Given a weighted directed acyclic graph whose edge weights can change in an arbitrary (adversarial) way, a decision maker has to choose in each round of a game a path between two distinguished vertices such that the lo... |
Title: A neural network approach to ordinal regression |
Abstract: Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe a simple and effective approach to adapt a traditional neural network to learn ordinal categories. Our approach is a generalization of the perceptron method for ordinal regression.... |
Title: High-dimensional variable selection |
Abstract: This paper explores the following question: what kind of statistical guarantees can be given when doing variable selection in high-dimensional models? In particular, we look at the error rates and power of some multi-stage regression methods. In the first stage we fit a set of candidate models. In the second ... |
Title: Text Line Segmentation of Historical Documents: a Survey |
Abstract: There is a huge amount of historical documents in libraries and in various National Archives that have not been exploited electronically. Although automatic reading of complete pages remains, in most cases, a long-term objective, tasks such as word spotting, text/image alignment, authentication and extraction... |
Title: Parametric Learning and Monte Carlo Optimization |
Abstract: This paper uncovers and explores the close relationship between Monte Carlo Optimization of a parametrized integral (MCO), Parametric machine-Learning (PL), and `blackbox' or `oracle'-based optimization (BO). We make four contributions. First, we prove that MCO is mathematically identical to a broad class of ... |
Title: A Dynamic Algorithm for Blind Separation of Convolutive Sound Mixtures |
Abstract: We study an efficient dynamic blind source separation algorithm of convolutive sound mixtures based on updating statistical information in the frequency domain, andminimizing the support of time domain demixing filters by a weighted least square method. The permutation and scaling indeterminacies of separatio... |
Title: Calculating Valid Domains for BDD-Based Interactive Configuration |
Abstract: In these notes we formally describe the functionality of Calculating Valid Domains from the BDD representing the solution space of valid configurations. The formalization is largely based on the CLab configuration framework. |
Title: Preconditioned Temporal Difference Learning |
Abstract: This paper has been withdrawn by the author. This draft is withdrawn for its poor quality in english, unfortunately produced by the author when he was just starting his science route. Look at the ICML version instead: http://icml2008.cs.helsinki.fi/papers/111.pdf |
Title: Sparse Estimators and the Oracle Property, or the Return of Hodges' Estimator |
Abstract: We point out some pitfalls related to the concept of an oracle property as used in Fan and Li (2001, 2002, 2004) which are reminiscent of the well-known pitfalls related to Hodges' estimator. The oracle property is often a consequence of sparsity of an estimator. We show that any estimator satisfying a sparsi... |
Title: Can One Estimate The Unconditional Distribution of Post-Model-Selection Estimators? |
Abstract: We consider the problem of estimating the unconditional distribution of a post-model-selection estimator. The notion of a post-model-selection estimator here refers to the combined procedure resulting from first selecting a model (e.g., by a model selection criterion like AIC or by a hypothesis testing proced... |
Title: Exploiting Social Annotation for Automatic Resource Discovery |
Abstract: Information integration applications, such as mediators or mashups, that require access to information resources currently rely on users manually discovering and integrating them in the application. Manual resource discovery is a slow process, requiring the user to sift through results obtained via keyword-ba... |
Title: Personalizing Image Search Results on Flickr |
Abstract: The social media site Flickr allows users to upload their photos, annotate them with tags, submit them to groups, and also to form social networks by adding other users as contacts. Flickr offers multiple ways of browsing or searching it. One option is tag search, which returns all images tagged with a specif... |
Title: Unicast and Multicast Qos Routing with Soft Constraint Logic Programming |
Abstract: We present a formal model to represent and solve the unicast/multicast routing problem in networks with Quality of Service (QoS) requirements. To attain this, first we translate the network adapting it to a weighted graph (unicast) or and-or graph (multicast), where the weight on a connector corresponds to th... |
Title: A study of structural properties on profiles HMMs |
Abstract: Motivation: Profile hidden Markov Models (pHMMs) are a popular and very useful tool in the detection of the remote homologue protein families. Unfortunately, their performance is not always satisfactory when proteins are in the 'twilight zone'. We present HMMER-STRUCT, a model construction algorithm and tool ... |
Title: Introduction to Arabic Speech Recognition Using CMUSphinx System |
Abstract: In this paper Arabic was investigated from the speech recognition problem point of view. We propose a novel approach to build an Arabic Automated Speech Recognition System (ASR). This system is based on the open source CMU Sphinx-4, from the Carnegie Mellon University. CMU Sphinx is a large-vocabulary; speake... |
Title: A Note on the Inapproximability of Correlation Clustering |
Abstract: We consider inapproximability of the correlation clustering problem defined as follows: Given a graph $G = (V,E)$ where each edge is labeled either "+" (similar) or "-" (dissimilar), correlation clustering seeks to partition the vertices into clusters so that the number of pairs correctly (resp. incorrectly) ... |
Title: On the Computational Complexity of MCMC-based Estimators in Large Samples |
Abstract: In this paper we examine the implications of the statistical large sample theory for the computational complexity of Bayesian and quasi-Bayesian estimation carried out using Metropolis random walks. Our analysis is motivated by the Laplace-Bernstein-Von Mises central limit theorem, which states that in large ... |
Title: Arabic Speech Recognition System using CMU-Sphinx4 |
Abstract: In this paper we present the creation of an Arabic version of Automated Speech Recognition System (ASR). This system is based on the open source Sphinx-4, from the Carnegie Mellon University. Which is a speech recognition system based on discrete hidden Markov models (HMMs). We investigate the changes that mu... |
Title: Joint universal lossy coding and identification of stationary mixing sources |
Abstract: The problem of joint universal source coding and modeling, treated in the context of lossless codes by Rissanen, was recently generalized to fixed-rate lossy coding of finitely parametrized continuous-alphabet i.i.d. sources. We extend these results to variable-rate lossy block coding of stationary ergodic so... |
Title: Supervised Feature Selection via Dependence Estimation |
Abstract: We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The key idea is that good features should maximise such dependence. Feature selection for various supervised learning problems (includi... |
Title: Experimenting with recursive queries in database and logic programming systems |
Abstract: This paper considers the problem of reasoning on massive amounts of (possibly distributed) data. Presently, existing proposals show some limitations: \em (i) the quantity of data that can be handled contemporarily is limited, due to the fact that reasoning is generally carried out in main-memory; \em (ii) the... |
Title: 2D Path Solutions from a Single Layer Excitable CNN Model |
Abstract: An easily implementable path solution algorithm for 2D spatial problems, based on excitable/programmable characteristics of a specific cellular nonlinear network (CNN) model is presented and numerically investigated. The network is a single layer bioinspired model which was also implemented in CMOS technology... |
Title: Direct Optimization of Ranking Measures |
Abstract: Web page ranking and collaborative filtering require the optimization of sophisticated performance measures. Current Support Vector approaches are unable to optimize them directly and focus on pairwise comparisons instead. We present a new approach which allows direct optimization of the relevant loss functio... |
Title: General-Purpose Computing on a Semantic Network Substrate |
Abstract: This article presents a model of general-purpose computing on a semantic network substrate. The concepts presented are applicable to any semantic network representation. However, due to the standards and technological infrastructure devoted to the Semantic Web effort, this article is presented from this point... |
Title: Bayesian approach to rough set |
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