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Title: Learning Bayesian Networks with the bnlearn R Package |
Abstract: bnlearn is an R package which includes several algorithms for learning the structure of Bayesian networks with either discrete or continuous variables. Both constraint-based and score-based algorithms are implemented, and can use the functionality provided by the snow package to improve their performance via ... |
Title: Gabor wavelet analysis and the fractional Hilbert transform |
Abstract: We propose an amplitude-phase representation of the dual-tree complex wavelet transform (DT-CWT) which provides an intuitive interpretation of the associated complex wavelet coefficients. The representation, in particular, is based on the shifting action of the group of fractional Hilbert transforms (fHT) whi... |
Title: Self-consistent method for density estimation |
Abstract: The estimation of a density profile from experimental data points is a challenging problem, usually tackled by plotting a histogram. Prior assumptions on the nature of the density, from its smoothness to the specification of its form, allow the design of more accurate estimation procedures, such as Maximum Li... |
Title: Fast adaptive elliptical filtering using box splines |
Abstract: We demonstrate that it is possible to filter an image with an elliptic window of varying size, elongation and orientation with a fixed computational cost per pixel. Our method involves the application of a suitable global pre-integrator followed by a pointwise-adaptive localization mesh. We present the basic ... |
Title: Learning networks from high dimensional binary data: An application to genomic instability data |
Abstract: Genomic instability, the propensity of aberrations in chromosomes, plays a critical role in the development of many diseases. High throughput genotyping experiments have been performed to study genomic instability in diseases. The output of such experiments can be summarized as high dimensional binary vectors... |
Title: A Dynamic Boundary Guarding Problem with Translating Targets |
Abstract: We introduce a problem in which a service vehicle seeks to guard a deadline (boundary) from dynamically arriving mobile targets. The environment is a rectangle and the deadline is one of its edges. Targets arrive continuously over time on the edge opposite the deadline, and move towards the deadline at a fixe... |
Title: A simple sketching algorithm for entropy estimation |
Abstract: We consider the problem of approximating the empirical Shannon entropy of a high-frequency data stream under the relaxed strict-turnstile model, when space limitations make exact computation infeasible. An equivalent measure of entropy is the Renyi entropy that depends on a constant alpha. This quantity can b... |
Title: An improved axiomatic definition of information granulation |
Abstract: To capture the uncertainty of information or knowledge in information systems, various information granulations, also known as knowledge granulations, have been proposed. Recently, several axiomatic definitions of information granulation have been introduced. In this paper, we try to improve these axiomatic d... |
Title: Numerical Comparison of Cusum and Shiryaev-Roberts Procedures for Detecting Changes in Distributions |
Abstract: The CUSUM procedure is known to be optimal for detecting a change in distribution under a minimax scenario, whereas the Shiryaev-Roberts procedure is optimal for detecting a change that occurs at a distant time horizon. As a simpler alternative to the conventional Monte Carlo approach, we propose a numerical ... |
Title: ABC-LogitBoost for Multi-class Classification |
Abstract: We develop abc-logitboost, based on the prior work on abc-boost and robust logitboost. Our extensive experiments on a variety of datasets demonstrate the considerable improvement of abc-logitboost over logitboost and abc-mart. |
Title: Decentralized Sequential Hypothesis Testing using Asynchronous Communication |
Abstract: We present a test for the problem of decentralized sequential hypothesis testing, which is asymptotically optimum. By selecting a suitable sampling mechanism at each sensor, communication between sensors and fusion center is asynchronous and limited to 1-bit data. The proposed SPRT-like test turns out to be o... |
Title: Co-occurrence Matrix and Fractal Dimension for Image Segmentation |
Abstract: One of the most important tasks in image processing problem and machine vision is object recognition, and the success of many proposed methods relies on a suitable choice of algorithm for the segmentation of an image. This paper focuses on how to apply texture operators based on the concept of fractal dimensi... |
Title: Handwritten Farsi Character Recognition using Artificial Neural Network |
Abstract: Neural Networks are being used for character recognition from last many years but most of the work was confined to English character recognition. Till date, a very little work has been reported for Handwritten Farsi Character recognition. In this paper, we have made an attempt to recognize handwritten Farsi c... |
Title: Multiple Retrieval Models and Regression Models for Prior Art Search |
Abstract: This paper presents the system called PATATRAS (PATent and Article Tracking, Retrieval and AnalysiS) realized for the IP track of CLEF 2009. Our approach presents three main characteristics: 1. The usage of multiple retrieval models (KL, Okapi) and term index definitions (lemma, phrase, concept) for the three... |
Title: Geometry of the restricted Boltzmann machine |
Abstract: The restricted Boltzmann machine is a graphical model for binary random variables. Based on a complete bipartite graph separating hidden and observed variables, it is the binary analog to the factor analysis model. We study this graphical model from the perspectives of algebraic statistics and tropical geomet... |
Title: An OLAC Extension for Dravidian Languages |
Abstract: OLAC was founded in 2000 for creating online databases of language resources. This paper intends to review the bottom-up distributed character of the project and proposes an extension of the architecture for Dravidian languages. An ontological structure is considered for effective natural language processing ... |
Title: Connecting tables with zero-one entries by a subset of a Markov basis |
Abstract: We discuss connecting tables with zero-one entries by a subset of a Markov basis. In this paper, as a Markov basis we consider the Graver basis, which corresponds to the unique minimal Markov basis for the Lawrence lifting of the original configuration. Since the Graver basis tends to be large, it is of inter... |
Title: The eel-like robot |
Abstract: The aim of this project is to design, study and build an "eel-like robot" prototype able to swim in three dimensions. The study is based on the analysis of eel swimming and results in the realization of a prototype with 12 vertebrae, a skin and a head with two fins. To reach these objectives, a multidisciplin... |
Title: Bayesian orthogonal component analysis for sparse representation |
Abstract: This paper addresses the problem of identifying a lower dimensional space where observed data can be sparsely represented. This under-complete dictionary learning task can be formulated as a blind separation problem of sparse sources linearly mixed with an unknown orthogonal mixing matrix. This issue is formu... |
Title: On the optimal design of parallel robots taking into account their deformations and natural frequencies |
Abstract: This paper discusses the utility of using simple stiffness and vibrations models, based on the Jacobian matrix of a manipulator and only the rigidity of the actuators, whenever its geometry is optimised. In many works, these simplified models are used to propose optimal design of robots. However, the elastici... |
Title: On the Internal Topological Structure of Plane Regions |
Abstract: The study of topological information of spatial objects has for a long time been a focus of research in disciplines like computational geometry, spatial reasoning, cognitive science, and robotics. While the majority of these researches emphasised the topological relations between spatial objects, this work st... |
Title: Reasoning with Topological and Directional Spatial Information |
Abstract: Current research on qualitative spatial representation and reasoning mainly focuses on one single aspect of space. In real world applications, however, multiple spatial aspects are often involved simultaneously. This paper investigates problems arising in reasoning with combined topological and directional in... |
Title: Reasoning about Cardinal Directions between Extended Objects |
Abstract: Direction relations between extended spatial objects are important commonsense knowledge. Recently, Goyal and Egenhofer proposed a formal model, known as Cardinal Direction Calculus (CDC), for representing direction relations between connected plane regions. CDC is perhaps the most expressive qualitative calc... |
Title: A theory of intelligence: networked problem solving in animal societies |
Abstract: A society's single emergent, increasing intelligence arises partly from the thermodynamic advantages of networking the innate intelligence of different individuals, and partly from the accumulation of solved problems. Economic growth is proportional to the square of the network entropy of a society's populati... |
Title: Latin hypercube sampling with inequality constraints |
Abstract: In some studies requiring predictive and CPU-time consuming numerical models, the sampling design of the model input variables has to be chosen with caution. For this purpose, Latin hypercube sampling has a long history and has shown its robustness capabilities. In this paper we propose and discuss a new algo... |
Title: Monte Carlo Methods in Statistics |
Abstract: Monte Carlo methods are now an essential part of the statistician's toolbox, to the point of being more familiar to graduate students than the measure theoretic notions upon which they are based! We recall in this note some of the advances made in the design of Monte Carlo techniques towards their use in Stat... |
Title: Rare-Allele Detection Using Compressed Se(que)nsing |
Abstract: Detection of rare variants by resequencing is important for the identification of individuals carrying disease variants. Rapid sequencing by new technologies enables low-cost resequencing of target regions, although it is still prohibitive to test more than a few individuals. In order to improve cost trade-of... |
Title: Kinematic analysis of a class of analytic planar 3-RPR parallel manipulators |
Abstract: A class of analytic planar 3-RPR manipulators is analyzed in this paper. These manipulators have congruent base and moving platforms and the moving platform is rotated of 180 deg about an axis in the plane. The forward kinematics is reduced to the solution of a 3rd-degree polynomial and a quadratic equation i... |
Title: Scale-Based Gaussian Coverings: Combining Intra and Inter Mixture Models in Image Segmentation |
Abstract: By a "covering" we mean a Gaussian mixture model fit to observed data. Approximations of the Bayes factor can be availed of to judge model fit to the data within a given Gaussian mixture model. Between families of Gaussian mixture models, we propose the R\'enyi quadratic entropy as an excellent and tractable ... |
Title: Advances in Feature Selection with Mutual Information |
Abstract: The selection of features that are relevant for a prediction or classification problem is an important problem in many domains involving high-dimensional data. Selecting features helps fighting the curse of dimensionality, improving the performances of prediction or classification methods, and interpreting th... |
Title: Median topographic maps for biomedical data sets |
Abstract: Median clustering extends popular neural data analysis methods such as the self-organizing map or neural gas to general data structures given by a dissimilarity matrix only. This offers flexible and robust global data inspection methods which are particularly suited for a variety of data as occurs in biomedic... |
Title: On Planning with Preferences in HTN |
Abstract: In this paper, we address the problem of generating preferred plans by combining the procedural control knowledge specified by Hierarchical Task Networks (HTNs) with rich qualitative user preferences. The outcome of our work is a language for specifyin user preferences, tailored to HTN planning, together with... |
Title: Efficient algorithms for training the parameters of hidden Markov models using stochastic expectation maximization EM training and Viterbi training |
Abstract: Background: Hidden Markov models are widely employed by numerous bioinformatics programs used today. Applications range widely from comparative gene prediction to time-series analyses of micro-array data. The parameters of the underlying models need to be adjusted for specific data sets, for example the genom... |
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