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Abstract: The joint cumulative distribution function for order statistics arising from several different populations is given in terms of the distribution function of the populations. The computational cost of the formula in the case of two populations is still exponential in the worst case, but it is a dramatic improv... |
Title: Efficient independent component analysis |
Abstract: Independent component analysis (ICA) has been widely used for blind source separation in many fields such as brain imaging analysis, signal processing and telecommunication. Many statistical techniques based on M-estimates have been proposed for estimating the mixing matrix. Recently, several nonparametric me... |
Title: Truecluster matching |
Abstract: Cluster matching by permuting cluster labels is important in many clustering contexts such as cluster validation and cluster ensemble techniques. The classic approach is to minimize the euclidean distance between two cluster solutions which induces inappropriate stability in certain settings. Therefore, we pr... |
Title: Network tomography based on 1-D projections |
Abstract: Network tomography has been regarded as one of the most promising methodologies for performance evaluation and diagnosis of the massive and decentralized Internet. This paper proposes a new estimation approach for solving a class of inverse problems in network tomography, based on marginal distributions of a ... |
Title: Mixed membership stochastic blockmodels |
Abstract: Observations consisting of measurements on relationships for pairs of objects arise in many settings, such as protein interaction and gene regulatory networks, collections of author-recipient email, and social networks. Analyzing such data with probabilisic models can be delicate because the simple exchangeab... |
Title: Loop corrections for message passing algorithms in continuous variable models |
Abstract: In this paper we derive the equations for Loop Corrected Belief Propagation on a continuous variable Gaussian model. Using the exactness of the averages for belief propagation for Gaussian models, a different way of obtaining the covariances is found, based on Belief Propagation on cavity graphs. We discuss t... |
Title: Modeling Epidemic Spread in Synthetic Populations - Virtual Plagues in Massively Multiplayer Online Games |
Abstract: A virtual plague is a process in which a behavior-affecting property spreads among characters in a Massively Multiplayer Online Game (MMOG). The MMOG individuals constitute a synthetic population, and the game can be seen as a form of interactive executable model for studying disease spread, albeit of a very ... |
Title: Variable Selection Incorporating Prior Constraint Information into Lasso |
Abstract: We propose the variable selection procedure incorporating prior constraint information into lasso. The proposed procedure combines the sample and prior information, and selects significant variables for responses in a narrower region where the true parameters lie. It increases the efficiency to choose the tru... |
Title: Local Area Damage Detection in Composite Structures Using Piezoelectric Transducers |
Abstract: An integrated and automated smart structures approach for structural health monitoring is presented, utilizing an array of piezoelectric transducers attached to or embedded within the structure for both actuation and sensing. The system actively interrogates the structure via broadband excitation of multiple ... |
Title: Recursive n-gram hashing is pairwise independent, at best |
Abstract: Many applications use sequences of n consecutive symbols (n-grams). Hashing these n-grams can be a performance bottleneck. For more speed, recursive hash families compute hash values by updating previous values. We prove that recursive hash families cannot be more than pairwise independent. While hashing by i... |
Title: Modeling Computations in a Semantic Network |
Abstract: Semantic network research has seen a resurgence from its early history in the cognitive sciences with the inception of the Semantic Web initiative. The Semantic Web effort has brought forth an array of technologies that support the encoding, storage, and querying of the semantic network data structure at the ... |
Title: The M-estimator in a multi-phase random nonlinear model |
Abstract: This paper considers M-estimation of a nonlinear regression model with multiple change-points occuring at unknown times. The multi-phase random design regression model, discontinuous in each change-point, have an arbitrary error $\epsilon$. In the case when the number of jumps is known, the M-estimator of loc... |
Title: Automatic Detection of Pulmonary Embolism using Computational Intelligence |
Abstract: This article describes the implementation of a system designed to automatically detect the presence of pulmonary embolism in lung scans. These images are firstly segmented, before alignment and feature extraction using PCA. The neural network was trained using the Hybrid Monte Carlo method, resulting in a com... |
Title: Challenges and Opportunities of Evolutionary Robotics |
Abstract: Robotic hardware designs are becoming more complex as the variety and number of on-board sensors increase and as greater computational power is provided in ever-smaller packages on-board robots. These advances in hardware, however, do not automatically translate into better software for controlling complex ro... |
Title: Virtual Sensor Based Fault Detection and Classification on a Plasma Etch Reactor |
Abstract: The SEMATECH sponsored J-88-E project teaming Texas Instruments with NeuroDyne (et al.) focused on Fault Detection and Classification (FDC) on a Lam 9600 aluminum plasma etch reactor, used in the process of semiconductor fabrication. Fault classification was accomplished by implementing a series of virtual se... |
Title: Compressed Regression |
Abstract: Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse data. This line of work shows that $\ell_1$-regularized least squares regression can accurately estimate a sparse linear model fro... |
Title: A Novel Model of Working Set Selection for SMO Decomposition Methods |
Abstract: In the process of training Support Vector Machines (SVMs) by decomposition methods, working set selection is an important technique, and some exciting schemes were employed into this field. To improve working set selection, we propose a new model for working set selection in sequential minimal optimization (S... |
Title: Construction of Bayesian Deformable Models via Stochastic Approximation Algorithm: A Convergence Study |
Abstract: The problem of the definition and the estimation of generative models based on deformable templates from raw data is of particular importance for modelling non aligned data affected by various types of geometrical variability. This is especially true in shape modelling in the computer vision community or in p... |
Title: Epistemic Analysis of Strategic Games with Arbitrary Strategy Sets |
Abstract: We provide here an epistemic analysis of arbitrary strategic games based on the possibility correspondences. Such an analysis calls for the use of transfinite iterations of the corresponding operators. Our approach is based on Tarski's Fixpoint Theorem and applies both to the notions of rationalizability and ... |
Title: Design, Implementation, and Cooperative Coevolution of an Autonomous/ Teleoperated Control System for a Serpentine Robotic Manipulator |
Abstract: Design, implementation, and machine learning issues associated with developing a control system for a serpentine robotic manipulator are explored. The controller developed provides autonomous control of the serpentine robotic manipulatorduring operation of the manipulator within an enclosed environment such a... |
Title: Power-law distributions in empirical data |
Abstract: Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the detection and characterization of power laws is complicated by the large fluctuations that occur in the tail of the distribution... |
Title: Automatically Restructuring Practice Guidelines using the GEM DTD |
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: Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models |
Abstract: A Bayesian approach is used to estimate the covariance matrix of Gaussian data. Ideas from Gaussian graphical models and model selection are used to construct a prior for the covariance matrix that is a mixture over all decomposable graphs. For this prior the probability of each graph size is specified by the... |
Title: Temporal Reasoning without Transitive Tables |
Abstract: Representing and reasoning about qualitative temporal information is an essential part of many artificial intelligence tasks. Lots of models have been proposed in the litterature for representing such temporal information. All derive from a point-based or an interval-based framework. One fundamental reasoning... |
Title: Sensitivity of principal Hessian direction analysis |
Abstract: We provide sensitivity comparisons for two competing versions of the dimension reduction method principal Hessian directions (pHd). These comparisons consider the effects of small perturbations on the estimation of the dimension reduction subspace via the influence function. We show that the two versions of p... |
Title: Coherence and phase synchronization: generalization to pairs of multivariate time series, and removal of zero-lag contributions |
Abstract: Coherence and phase synchronization between time series corresponding to different spatial locations are usually interpreted as indicators of the connectivity between locations. In neurophysiology, time series of electric neuronal activity are essential for studying brain interconnectivity. Such signals can e... |
Title: Towards understanding and modelling office daily life |
Abstract: Measuring and modeling human behavior is a very complex task. In this paper we present our initial thoughts on modeling and automatic recognition of some human activities in an office. We argue that to successfully model human activities, we need to consider both individual behavior and group dynamics. To dem... |
Title: Getting started in probabilistic graphical models |
Abstract: Probabilistic graphical models (PGMs) have become a popular tool for computational analysis of biological data in a variety of domains. But, what exactly are they and how do they work? How can we use PGMs to discover patterns that are biologically relevant? And to what extent can PGMs help us formulate new hy... |
Title: Some questions of Monte-Carlo modeling on nontrivial bundles |
Abstract: In this work are considered some questions of Monte-Carlo modeling on nontrivial bundles. As a basic example is used problem of generation of straight lines in 3D space, related with modeling of interaction of a solid body with a flux of particles and with some other tasks. Space of lines used in given model ... |
Title: Statistical testing procedure for the interaction effects of several controllable factors in two-valued input-output systems |
Abstract: Suppose several two-valued input-output systems are designed by setting the levels of several controllable factors. For this situation, Taguchi method has proposed to assign the controllable factors to the orthogonal array and use ANOVA model for the standardized SN ratio, which is a natural measure for evalu... |
Title: A tutorial on conformal prediction |
Abstract: Conformal prediction uses past experience to determine precise levels of confidence in new predictions. Given an error probability $\epsilon$, together with a method that makes a prediction $$ of a label $y$, it produces a set of labels, typically containing $$, that also contains $y$ with probability $1-\eps... |
Title: Separating populations with wide data: A spectral analysis |
Abstract: In this paper, we consider the problem of partitioning a small data sample drawn from a mixture of $k$ product distributions. We are interested in the case that individual features are of low average quality $\gamma$, and we want to use as few of them as possible to correctly partition the sample. We analyze ... |
Title: Undercomplete Blind Subspace Deconvolution via Linear Prediction |
Abstract: We present a novel solution technique for the blind subspace deconvolution (BSSD) problem, where temporal convolution of multidimensional hidden independent components is observed and the task is to uncover the hidden components using the observation only. We carry out this task for the undercomplete case (uB... |
Title: The SSM Toolbox for Matlab |
Abstract: State Space Models (SSM) is a MATLAB 7.0 software toolbox for doing time series analysis by state space methods. The software features fully interactive construction and combination of models, with support for univariate and multivariate models, complex time-varying (dynamic) models, non-Gaussian models, and ... |
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