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Title: Fast stable direct fitting and smoothness selection for Generalized Additive Models |
Abstract: Existing computationally efficient methods for penalized likelihood GAM fitting employ iterative smoothness selection on working linear models (or working mixed models). Such schemes fail to converge for a non-negligible proportion of models, with failure being particularly frequent in the presence of concurv... |
Title: Blind Minimax Estimation |
Abstract: We consider the linear regression problem of estimating an unknown, deterministic parameter vector based on measurements corrupted by colored Gaussian noise. We present and analyze blind minimax estimators (BMEs), which consist of a bounded parameter set minimax estimator, whose parameter set is itself estima... |
Title: Evolving Classifiers: Methods for Incremental Learning |
Abstract: The ability of a classifier to take on new information and classes by evolving the classifier without it having to be fully retrained is known as incremental learning. Incremental learning has been successfully applied to many classification problems, where the data is changing and is not all available at onc... |
Title: Classification of Images Using Support Vector Machines |
Abstract: Support Vector Machines (SVMs) are a relatively new supervised classification technique to the land cover mapping community. They have their roots in Statistical Learning Theory and have gained prominence because they are robust, accurate and are effective even when using a small training sample. By their nat... |
Title: Fitness landscape of the cellular automata majority problem: View from the Olympus |
Abstract: In this paper we study cellular automata (CAs) that perform the computational Majority task. This task is a good example of what the phenomenon of emergence in complex systems is. We take an interest in the reasons that make this particular fitness landscape a difficult one. The first goal is to study the lan... |
Title: Local search heuristics: Fitness Cloud versus Fitness Landscape |
Abstract: This paper introduces the concept of fitness cloud as an alternative way to visualize and analyze search spaces than given by the geographic notion of fitness landscape. It is argued that the fitness cloud concept overcomes several deficiencies of the landscape representation. Our analysis is based on the cor... |
Title: Measuring the Evolvability Landscape to study Neutrality |
Abstract: This theoretical work defines the measure of autocorrelation of evolvability in the context of neutral fitness landscape. This measure has been studied on the classical MAX-SAT problem. This work highlight a new characteristic of neutral fitness landscapes which allows to design new adapted metaheuristic. |
Title: From Texts to Structured Documents: The Case of Health Practice Guidelines |
Abstract: This paper describes a system capable of semi-automatically filling an XML template from free texts in the clinical domain (practice guidelines). The XML template includes semantic information not explicitly encoded in the text (pairs of conditions and actions/recommendations). Therefore, there is a need to c... |
Title: Inferring Diversity: Life After Shannon |
Abstract: The diversity of a community that cannot be fully counted must be inferred. The two preeminent inference methods are the MaxEnt method, which uses information in the form of constraints and Bayes' rule which uses information in the form of data. It has been shown that these two methods are special cases of th... |
Title: Markov basis for design of experiments with three-level factors |
Abstract: We consider Markov basis arising from fractional factorial designs with three-level factors. Once we have a Markov basis, $p$ values for various conditional tests are estimated by the Markov chain Monte Carlo procedure. For designed experiments with a single count observation for each run, we formulate a gene... |
Title: Mining for trees in a graph is NP-complete |
Abstract: Mining for trees in a graph is shown to be NP-complete. |
Title: Bio-linguistic transition and Baldwin effect in an evolutionary naming-game model |
Abstract: We examine an evolutionary naming-game model where communicating agents are equipped with an evolutionarily selected learning ability. Such a coupling of biological and linguistic ingredients results in an abrupt transition: upon a small change of a model control parameter a poorly communicating group of ling... |
Title: Lagrangian Relaxation for MAP Estimation in Graphical Models |
Abstract: We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an intractable estimation problem as one defined on a more tractable graph, but subject to additional constraints. Relaxing these constraints gives... |
Title: Graph rigidity, Cyclic Belief Propagation and Point Pattern Matching |
Abstract: A recent paper proposed a provably optimal, polynomial time method for performing near-isometric point pattern matching by means of exact probabilistic inference in a chordal graphical model. Their fundamental result is that the chordal graph in question is shown to be globally rigid, implying that exact infe... |
Title: Zipf's Law and Avoidance of Excessive Synonymy |
Abstract: Zipf's law states that if words of language are ranked in the order of decreasing frequency in texts, the frequency of a word is inversely proportional to its rank. It is very robust as an experimental observation, but to date it escaped satisfactory theoretical explanation. We suggest that Zipf's law may ari... |
Title: Evaluation experiments on related terms search in Wikipedia: Information Content and Adapted HITS (In Russian) |
Abstract: The classification of metrics and algorithms search for related terms via WordNet, Roget's Thesaurus, and Wikipedia was extended to include adapted HITS algorithm. Evaluation experiments on Information Content and adapted HITS algorithm are described. The test collection of Russian word pairs with human-assig... |
Title: Quality assessment for short oligonucleotide microarray data |
Abstract: Quality of microarray gene expression data has emerged as a new research topic. As in other areas, microarray quality is assessed by comparing suitable numerical summaries across microarrays, so that outliers and trends can be visualized, and poor quality arrays or variable quality sets of arrays can be ident... |
Title: Optimising the topology of complex neural networks |
Abstract: In this paper, we study instances of complex neural networks, i.e. neural netwo rks with complex topologies. We use Self-Organizing Map neural networks whose n eighbourhood relationships are defined by a complex network, to classify handwr itten digits. We show that topology has a small impact on performance ... |
Title: On the role of autocorrelations in texts |
Abstract: The task of finding a criterion allowing to distinguish a text from an arbitrary set of words is rather relevant in itself, for instance, in the aspect of development of means for internet-content indexing or separating signals and noise in communication channels. The Zipf law is currently considered to be th... |
Title: On the fractal nature of mutual relevance sequences in the Internet news message flows |
Abstract: In the task of information retrieval the term relevance is taken to mean formal conformity of a document given by the retrieval system to user's information query. As a rule, the documents found by the retrieval system should be submitted to the user in a certain order. Therefore, a retrieval perceived as a s... |
Title: High-Order Nonparametric Belief-Propagation for Fast Image Inpainting |
Abstract: In this paper, we use belief-propagation techniques to develop fast algorithms for image inpainting. Unlike traditional gradient-based approaches, which may require many iterations to converge, our techniques achieve competitive results after only a few iterations. On the other hand, while belief-propagation ... |
Title: The Theory of Unified Relativity for a Biovielectroluminescence Phenomenon via Fly's Visual and Imaging System |
Abstract: The elucidation upon fly's neuronal patterns as a link to computer graphics and memory cards I/O's, is investigated for the phenomenon by propounding a unified theory of Einstein's two known relativities. It is conclusive that flies could contribute a certain amount of neuromatrices indicating an imagery func... |
Title: Prediction with expert advice for the Brier game |
Abstract: We show that the Brier game of prediction is mixable and find the optimal learning rate and substitution function for it. The resulting prediction algorithm is applied to predict results of football and tennis matches. The theoretical performance guarantee turns out to be rather tight on these data sets, espe... |
Title: Structured variable selection in support vector machines |
Abstract: When applying the support vector machine (SVM) to high-dimensional classification problems, we often impose a sparse structure in the SVM to eliminate the influences of the irrelevant predictors. The lasso and other variable selection techniques have been successfully used in the SVM to perform automatic vari... |
Title: Colour image segmentation by the vector-valued Allen-Cahn phase-field model: a multigrid solution |
Abstract: We propose a new method for the numerical solution of a PDE-driven model for colour image segmentation and give numerical examples of the results. The method combines the vector-valued Allen-Cahn phase field equation with initial data fitting terms. This method is known to be closely related to the Mumford-Sh... |
Title: The nested Chinese restaurant process and Bayesian nonparametric inference of topic hierarchies |
Abstract: We present the nested Chinese restaurant process (nCRP), a stochastic process which assigns probability distributions to infinitely-deep, infinitely-branching trees. We show how this stochastic process can be used as a prior distribution in a Bayesian nonparametric model of document collections. Specifically,... |
Title: Control and Monitoring System for Modular Wireless Robot |
Abstract: We introduce our concept on the modular wireless robot consisting of three main modules : main unit, data acquisition and data processing modules. We have developed a generic prototype with an integrated control and monitoring system to enhance its flexibility, and to enable simple operation through a web-bas... |
Title: Computation of expansions for the maximum likelihood estimator and its distribution function |
Abstract: In this paper, insight is given in the techniques used to compute asymptotic expansions. In a broad fashion the technique is described. Most of the results apply to the paper "An expansion for the maximum likelihood estimator and its distribution function", which will be submitted. |
Title: Semantic distillation: a method for clustering objects by their contextual specificity |
Abstract: Techniques for data-mining, latent semantic analysis, contextual search of databases, etc. have long ago been developed by computer scientists working on information retrieval (IR). Experimental scientists, from all disciplines, having to analyse large collections of raw experimental data (astronomical, physi... |
Title: What's in a Name? |
Abstract: This paper describes experiments on identifying the language of a single name in isolation or in a document written in a different language. A new corpus has been compiled and made available, matching names against languages. This corpus is used in a series of experiments measuring the performance of general ... |
Title: Demographic growth and the distribution of language sizes |
Abstract: It is argued that the present log-normal distribution of language sizes is, to a large extent, a consequence of demographic dynamics within the population of speakers of each language. A two-parameter stochastic multiplicative process is proposed as a model for the population dynamics of individual languages,... |
Title: Lossless Representation of Graphs using Distributions |
Abstract: We consider complete graphs with edge weights and/or node weights taking values in some set. In the first part of this paper, we show that a large number of graphs are completely determined, up to isomorphism, by the distribution of their sub-triangles. In the second part, we propose graph representations in ... |
Title: A Heuristic Routing Mechanism Using a New Addressing Scheme |
Abstract: Current methods of routing are based on network information in the form of routing tables, in which routing protocols determine how to update the tables according to the network changes. Despite the variability of data in routing tables, node addresses are constant. In this paper, we first introduce the new c... |
Title: Ratios: A short guide to confidence limits and proper use |
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