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Title: From formulas to cirquents in computability logic |
Abstract: Computability logic (CoL) (see http://www.cis.upenn.edu/ giorgi/cl.html) is a recently introduced semantical platform and ambitious program for redeveloping logic as a formal theory of computability, as opposed to the formal theory of truth that logic has more traditionally been. Its expressions represent int... |
Title: Characterising equilibrium logic and nested logic programs: Reductions and complexity |
Abstract: Equilibrium logic is an approach to nonmonotonic reasoning that extends the stable-model and answer-set semantics for logic programs. In particular, it includes the general case of nested logic programs, where arbitrary Boolean combinations are permitted in heads and bodies of rules, as special kinds of theor... |
Title: Reconstructing DNA copy number by penalized estimation and imputation |
Abstract: Recent advances in genomics have underscored the surprising ubiquity of DNA copy number variation (CNV). Fortunately, modern genotyping platforms also detect CNVs with fairly high reliability. Hidden Markov models and algorithms have played a dominant role in the interpretation of CNV data. Here we explore CN... |
Title: A Neural Network Classifier of Volume Datasets |
Abstract: Many state-of-the art visualization techniques must be tailored to the specific type of dataset, its modality (CT, MRI, etc.), the recorded object or anatomical region (head, spine, abdomen, etc.) and other parameters related to the data acquisition process. While parts of the information (imaging modality an... |
Title: Properties of quasi-alphabetic tree bimorphisms |
Abstract: We study the class of quasi-alphabetic relations, i.e., tree transformations defined by tree bimorphisms with two quasi-alphabetic tree homomorphisms and a regular tree language. We present a canonical representation of these relations; as an immediate consequence, we get the closure under union. Also, we sho... |
Title: Without a 'doubt'? Unsupervised discovery of downward-entailing operators |
Abstract: An important part of textual inference is making deductions involving monotonicity, that is, determining whether a given assertion entails restrictions or relaxations of that assertion. For instance, the statement 'We know the epidemic spread quickly' does not entail 'We know the epidemic spread quickly via f... |
Title: Exact Indexing for Massive Time Series Databases under Time Warping Distance |
Abstract: Among many existing distance measures for time series data, Dynamic Time Warping (DTW) distance has been recognized as one of the most accurate and suitable distance measures due to its flexibility in sequence alignment. However, DTW distance calculation is computationally intensive. Especially in very large ... |
Title: Observed Universality of Phase Transitions in High-Dimensional Geometry, with Implications for Modern Data Analysis and Signal Processing |
Abstract: We review connections between phase transitions in high-dimensional combinatorial geometry and phase transitions occurring in modern high-dimensional data analysis and signal processing. In data analysis, such transitions arise as abrupt breakdown of linear model selection, robust data fitting or compressed s... |
Title: Bayesian History Reconstruction of Complex Human Gene Clusters on a Phylogeny |
Abstract: Clusters of genes that have evolved by repeated segmental duplication present difficult challenges throughout genomic analysis, from sequence assembly to functional analysis. Improved understanding of these clusters is of utmost importance, since they have been shown to be the source of evolutionary innovatio... |
Title: Evaluating Health Risk Models |
Abstract: Interest in targeted disease prevention has stimulated development of models that assign risks to individuals, using their personal covariates. We need to evaluate these models, and to quantify the gains achieved by expanding a model with additional covariates. We describe several performance measures for ris... |
Title: Maximal digital straight segments and convergence of discrete geometric estimators |
Abstract: Discrete geometric estimators approach geometric quantities on digitized shapes without any knowledge of the continuous shape. A classical yet difficult problem is to show that an estimator asymptotically converges toward the true geometric quantity as the resolution increases. We study here the convergence o... |
Title: Coding cells of digital spaces: a framework to write generic digital topology algorithms |
Abstract: This paper proposes a concise coding of the cells of n-dimensional finite regular grids. It induces a simple, generic and efficient framework for implementing classical digital topology data structures and algorithms. Discrete subsets of multidimensional images (e.g. regions, digital surfaces, cubical cell co... |
Title: Combinatorial pyramids and discrete geometry for energy-minimizing segmentation |
Abstract: This paper defines the basis of a new hierarchical framework for segmentation algorithms based on energy minimization schemes. This new framework is based on two formal tools. First, a combinatorial pyramid encode efficiently a hierarchy of partitions. Secondly, discrete geometric estimators measure precisely... |
Title: What Does Artificial Life Tell Us About Death? |
Abstract: Short philosophical essay |
Title: Employing Wikipedia's Natural Intelligence For Cross Language Information Retrieval |
Abstract: In this paper we present a novel method for retrieving information in languages other than that of the query. We use this technique in combination with existing traditional Cross Language Information Retrieval (CLIR) techniques to improve their results. This method has a number of advantages over traditional ... |
Title: Noisy Independent Factor Analysis Model for Density Estimation and Classification |
Abstract: We consider the problem of multivariate density estimation when the unknown density is assumed to follow a particular form of dimensionality reduction, a noisy independent factor analysis (IFA) model. In this model the data are generated by a number of latent independent components having unknown distribution... |
Title: Entropy Message Passing |
Abstract: The paper proposes a new message passing algorithm for cycle-free factor graphs. The proposed "entropy message passing" (EMP) algorithm may be viewed as sum-product message passing over the entropy semiring, which has previously appeared in automata theory. The primary use of EMP is to compute the entropy of ... |
Title: Testing for Homogeneity in Meta-Analysis I. The One Parameter Case: Standardized Mean Difference |
Abstract: Meta-analysis seeks to combine the results of several experiments in order to improve the accuracy of decisions. It is common to use a test for homogeneity to determine if the results of the several experiments are sufficiently similar to warrant their combination into an overall result. Cochran's Q statistic... |
Title: Mnesors for automatic control |
Abstract: Mnesors are defined as elements of a semimodule over the min-plus integers. This two-sorted structure is able to merge graduation properties of vectors and idempotent properties of boolean numbers, which makes it appropriate for hybrid systems. We apply it to the control of an inverted pendulum and design a f... |
Title: Deformable Model with a Complexity Independent from Image Resolution |
Abstract: We present a parametric deformable model which recovers image components with a complexity independent from the resolution of input images. The proposed model also automatically changes its topology and remains fully compatible with the general framework of deformable models. More precisely, the image space i... |
Title: Minimax rank estimation for subspace tracking |
Abstract: Rank estimation is a classical model order selection problem that arises in a variety of important statistical signal and array processing systems, yet is addressed relatively infrequently in the extant literature. Here we present sample covariance asymptotics stemming from random matrix theory, and bring the... |
Title: Semi-Myopic Sensing Plans for Value Optimization |
Abstract: We consider the following sequential decision problem. Given a set of items of unknown utility, we need to select one of as high a utility as possible (``the selection problem''). Measurements (possibly noisy) of item values prior to selection are allowed, at a known cost. The goal is to optimize the overall ... |
Title: Variable selection in high-dimensional linear models: partially faithful distributions and the PC-simple algorithm |
Abstract: We consider variable selection in high-dimensional linear models where the number of covariates greatly exceeds the sample size. We introduce the new concept of partial faithfulness and use it to infer associations between the covariates and the response. Under partial faithfulness, we develop a simplified ve... |
Title: Reduction algorithm for the NPMLE for the distribution function of bivariate interval censored data |
Abstract: We study computational aspects of the nonparametric maximum likelihood estimator (NPMLE) for the distribution function of bivariate interval censored data. The computation of the NPMLE consists of two steps: a parameter reduction step and an optimization step. In this paper we focus on the reduction step. We ... |
Title: Generation of Fractional Factorial Designs |
Abstract: The joint use of counting functions, Hilbert basis and Markov basis allows to define a procedure to generate all the fractions that satisfy a given set of constraints in terms of orthogonality. The general case of mixed level designs, without restrictions on the number of levels of each factor (like primes or... |
Title: Adaptive Regularization of Ill-Posed Problems: Application to Non-rigid Image Registration |
Abstract: We introduce an adaptive regularization approach. In contrast to conventional Tikhonov regularization, which specifies a fixed regularization operator, we estimate it simultaneously with parameters. From a Bayesian perspective we estimate the prior distribution on parameters assuming that it is close to some ... |
Title: AIS for Misbehavior Detection in Wireless Sensor Networks: Performance and Design Principles |
Abstract: A sensor network is a collection of wireless devices that are able to monitor physical or environmental conditions. These devices (nodes) are expected to operate autonomously, be battery powered and have very limited computational capabilities. This makes the task of protecting a sensor network against misbeh... |
Title: Transposable regularized covariance models with an application to missing data imputation |
Abstract: Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable, meaning that either the rows, columns or both can be treated as features. To model transposable data, we present a modification of the matrix-variate norma... |
Title: Semiparametric modeling of autonomous nonlinear dynamical systems with applications |
Abstract: In this paper, we propose a semi-parametric model for autonomous nonlinear dynamical systems and devise an estimation procedure for model fitting. This model incorporates subject-specific effects and can be viewed as a nonlinear semi-parametric mixed effects model. We also propose a computationally efficient ... |
Title: Finding Significant Subregions in Large Image Databases |
Abstract: Images have become an important data source in many scientific and commercial domains. Analysis and exploration of image collections often requires the retrieval of the best subregions matching a given query. The support of such content-based retrieval requires not only the formulation of an appropriate scori... |
Title: Forest Garrote |
Abstract: Variable selection for high-dimensional linear models has received a lot of attention lately, mostly in the context of l1-regularization. Part of the attraction is the variable selection effect: parsimonious models are obtained, which are very suitable for interpretation. In terms of predictive power, however... |
Title: The Statistical Analysis of fMRI Data |
Abstract: In recent years there has been explosive growth in the number of neuroimaging studies performed using functional Magnetic Resonance Imaging (fMRI). The field that has grown around the acquisition and analysis of fMRI data is intrinsically interdisciplinary in nature and involves contributions from researchers... |
Title: Two-Dimensional ARMA Modeling for Breast Cancer Detection and Classification |
Abstract: We propose a new model-based computer-aided diagnosis (CAD) system for tumor detection and classification (cancerous v.s. benign) in breast images. Specifically, we show that (x-ray, ultrasound and MRI) images can be accurately modeled by two-dimensional autoregressive-moving average (ARMA) random fields. We ... |
Title: How opinions are received by online communities: A case study on Amazon.com helpfulness votes |
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