text stringlengths 0 4.09k |
|---|
Title: Collective Construction of 2D Block Structures with Holes |
Abstract: In this paper we present algorithms for collective construction systems in which a large number of autonomous mobile robots trans- port modular building elements to construct a desired structure. We focus on building block structures subject to some physical constraints that restrict the order in which the bl... |
Title: Models for transcript quantification from RNA-Seq |
Abstract: RNA-Seq is rapidly becoming the standard technology for transcriptome analysis. Fundamental to many of the applications of RNA-Seq is the quantification problem, which is the accurate measurement of relative transcript abundances from the sequenced reads. We focus on this problem, and review many recently pub... |
Title: An expert system for detecting automobile insurance fraud using social network analysis |
Abstract: The article proposes an expert system for detection, and subsequent investigation, of groups of collaborating automobile insurance fraudsters. The system is described and examined in great detail, several technical difficulties in detecting fraud are also considered, for it to be applicable in practice. Oppos... |
Title: Translation-based Constraint Answer Set Solving |
Abstract: We solve constraint satisfaction problems through translation to answer set programming (ASP). Our reformulations have the property that unit-propagation in the ASP solver achieves well defined local consistency properties like arc, bound and range consistency. Experiments demonstrate the computational value ... |
Title: Understanding Exhaustive Pattern Learning |
Abstract: Pattern learning in an important problem in Natural Language Processing (NLP). Some exhaustive pattern learning (EPL) methods (Bod, 1992) were proved to be flawed (Johnson, 2002), while similar algorithms (Och and Ney, 2004) showed great advantages on other tasks, such as machine translation. In this article,... |
Title: Palette-colouring: a belief-propagation approach |
Abstract: We consider a variation of the prototype combinatorial-optimisation problem known as graph-colouring. Our optimisation goal is to colour the vertices of a graph with a fixed number of colours, in a way to maximise the number of different colours present in the set of nearest neighbours of each given vertex. T... |
Title: Testing the Equality of Covariance Operators in Functional Samples |
Abstract: We propose a robust test for the equality of the covariance structures in two functional samples. The test statistic has a chi-square asymptotic distribution with a known number of degrees of freedom, which depends on the level of dimension reduction needed to represent the data. Detailed analysis of the asym... |
Title: On the evolution of the instance level of DL-lite knowledge bases |
Abstract: Recent papers address the issue of updating the instance level of knowledge bases expressed in Description Logic following a model-based approach. One of the outcomes of these papers is that the result of updating a knowledge base K is generally not expressible in the Description Logic used to express K. In t... |
Title: Fast redshift clustering with the Baire (ultra) metric |
Abstract: The Baire metric induces an ultrametric on a dataset and is of linear computational complexity, contrasted with the standard quadratic time agglomerative hierarchical clustering algorithm. We apply the Baire distance to spectrometric and photometric redshifts from the Sloan Digital Sky Survey using, in this w... |
Title: Sampling decomposable graphs using a Markov chain on junction trees |
Abstract: Full Bayesian computational inference for model determination in undirected graphical models is currently restricted to decomposable graphs, except for problems of very small scale. In this paper we develop new, more efficient methodology for such inference, by making two contributions to the computational ge... |
Title: Posterior consistency in linear models under shrinkage priors |
Abstract: We investigate the asymptotic behavior of posterior distributions of regression coefficients in high-dimensional linear models as the number of dimensions grows with the number of observations. We show that the posterior distribution concentrates in neighborhoods of the true parameter under simple sufficient ... |
Title: Learning invariant features through local space contraction |
Abstract: We present in this paper a novel approach for training deterministic auto-encoders. We show that by adding a well chosen penalty term to the classical reconstruction cost function, we can achieve results that equal or surpass those attained by other regularized auto-encoders as well as denoising auto-encoders... |
Title: A Meshless Method for Variational Nonrigid 2-D Shape Registration |
Abstract: We present a method for nonrigid registration of 2-D geometric shapes. Our contribution is twofold. First, we extend the classic chamfer-matching energy to a variational functional. Secondly, we introduce a meshless deformation model that can handle significant high-curvature deformations. We represent 2-D sh... |
Title: A Generalization of the Skew-Normal Distribution: The Beta Skew-Normal |
Abstract: The aim of this article is to introduce a new family of distributions, which generalizes the skew normal distribution (SN). This new family, called Beta skew-normal (BSN), arises naturally when we consider the distributions of order statistics of the SN. The BSN can also be obtained as a special case of the B... |
Title: Distributed Self-Organization Of Swarms To Find Globally $\epsilon$-Optimal Routes To Locally Sensed Targets |
Abstract: The problem of near-optimal distributed path planning to locally sensed targets is investigated in the context of large swarms. The proposed algorithm uses only information that can be locally queried, and rigorous theoretical results on convergence, robustness, scalability are established, and effect of syst... |
Title: Algorithms and Complexity Results for Persuasive Argumentation |
Abstract: The study of arguments as abstract entities and their interaction as introduced by Dung (Artificial Intelligence 177, 1995) has become one of the most active research branches within Artificial Intelligence and Reasoning. A main issue for abstract argumentation systems is the selection of acceptable sets of a... |
Title: Improving digital signal interpolation: L2-optimal kernels with kernel-invariant interpolation speed |
Abstract: Interpolation is responsible for digital signal resampling and can significantly degrade the original signal quality if not done properly. For many years, optimal interpolation algorithms were sought within constrained classes of interpolation kernel functions. We derive a new family of unconstrained L2-optim... |
Title: Curved Gabor Filters for Fingerprint Image Enhancement |
Abstract: Gabor filters play an important role in many application areas for the enhancement of various types of images and the extraction of Gabor features. For the purpose of enhancing curved structures in noisy images, we introduce curved Gabor filters which locally adapt their shape to the direction of flow. These ... |
Title: Rank Minimization over Finite Fields: Fundamental Limits and Coding-Theoretic Interpretations |
Abstract: This paper establishes information-theoretic limits in estimating a finite field low-rank matrix given random linear measurements of it. These linear measurements are obtained by taking inner products of the low-rank matrix with random sensing matrices. Necessary and sufficient conditions on the number of mea... |
Title: Seeking Meaning in a Space Made out of Strokes, Radicals, Characters and Compounds |
Abstract: Chinese characters can be compared to a molecular structure: a character is analogous to a molecule, radicals are like atoms, calligraphic strokes correspond to elementary particles, and when characters form compounds, they are like molecular structures. In chemistry the conjunction of all of these structural... |
Title: Nonparametric survival analysis of epidemic data |
Abstract: This paper develops nonparametric methods for the survival analysis of epidemic data based on contact intervals. The contact interval from person i to person j is the time between the onset of infectiousness in i and infectious contact from i to j, where we define infectious contact as a contact sufficient to... |
Title: Intent Inference and Syntactic Tracking with GMTI Measurements |
Abstract: In conventional target tracking systems, human operators use the estimated target tracks to make higher level inference of the target behaviour/intent. This paper develops syntactic filtering algorithms that assist human operators by extracting spatial patterns from target tracks to identify suspicious/anomal... |
Title: Convex Approaches to Model Wavelet Sparsity Patterns |
Abstract: Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees(HMTs). However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix produces a linear mixing of the sim... |
Title: The Multivariate Watson Distribution: Maximum-Likelihood Estimation and other Aspects |
Abstract: This paper studies fundamental aspects of modelling data using multivariate Watson distributions. Although these distributions are natural for modelling axially symmetric data (i.e., unit vectors where $\pm \x$ are equivalent), for high-dimensions using them can be difficult. Why so? Largely because for Watso... |
Title: Phylogeny and geometry of languages from normalized Levenshtein distance |
Abstract: The idea that the distance among pairs of languages can be evaluated from lexical differences seems to have its roots in the work of the French explorer Dumont D'Urville. He collected comparative words lists of various languages during his voyages aboard the Astrolabe from 1826 to 1829 and, in his work about ... |
Title: Robust Clustering Using Outlier-Sparsity Regularization |
Abstract: Notwithstanding the popularity of conventional clustering algorithms such as K-means and probabilistic clustering, their clustering results are sensitive to the presence of outliers in the data. Even a few outliers can compromise the ability of these algorithms to identify meaningful hidden structures renderi... |
Title: Quantile Regression with Censoring and Endogeneity |
Abstract: In this paper, we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator combines Powell (1986) censored quantile regression (CQR) to deal with censoring, with a control variable approach to incorporate endogenous regressors. The ... |
Title: Scaled Sparse Linear Regression |
Abstract: Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the noise level via the mean residual square and scaling the penalty in proportion to the estimated noise level. ... |
Title: Compressive Network Analysis |
Abstract: Modern data acquisition routinely produces massive amounts of network data. Though many methods and models have been proposed to analyze such data, the research of network data is largely disconnected with the classical theory of statistical learning and signal processing. In this paper, we present a new fram... |
Title: Boolean Equi-propagation for Optimized SAT Encoding |
Abstract: We present an approach to propagation based solving, Boolean equi-propagation, where constraints are modelled as propagators of information about equalities between Boolean literals. Propagation based solving applies this information as a form of partial evaluation resulting in optimized SAT encodings. We dem... |
Title: Temporal Second Difference Traces |
Abstract: Q-learning is a reliable but inefficient off-policy temporal-difference method, backing up reward only one step at a time. Replacing traces, using a recency heuristic, are more efficient but less reliable. In this work, we introduce model-free, off-policy temporal difference methods that make better use of ex... |
Title: Performance Evaluation of Statistical Approaches for Text Independent Speaker Recognition Using Source Feature |
Abstract: This paper introduces the performance evaluation of statistical approaches for TextIndependent speaker recognition system using source feature. Linear prediction LP residual is used as a representation of excitation information in speech. The speaker-specific information in the excitation of voiced speech is ... |
Title: Positive Semidefinite Metric Learning Using Boosting-like Algorithms |
Abstract: The success of many machine learning and pattern recognition methods relies heavily upon the identification of an appropriate distance metric on the input data. It is often beneficial to learn such a metric from the input training data, instead of using a default one such as the Euclidean distance. In this wo... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.