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Title: Comparison of Support Vector Machine and Back Propagation Neural Network in Evaluating the Enterprise Financial Distress |
Abstract: Recently, applying the novel data mining techniques for evaluating enterprise financial distress has received much research alternation. Support Vector Machine (SVM) and back propagation neural (BPN) network has been applied successfully in many areas with excellent generalization results, such as rule extrac... |
Title: CLP-based protein fragment assembly |
Abstract: The paper investigates a novel approach, based on Constraint Logic Programming (CLP), to predict the 3D conformation of a protein via fragments assembly. The fragments are extracted by a preprocessor-also developed for this work- from a database of known protein structures that clusters and classifies the fra... |
Title: Synchronization and Control in Intrinsic and Designed Computation: An Information-Theoretic Analysis of Competing Models of Stochastic Computation |
Abstract: We adapt tools from information theory to analyze how an observer comes to synchronize with the hidden states of a finitary, stationary stochastic process. We show that synchronization is determined by both the process's internal organization and by an observer's model of it. We analyze these components using... |
Title: Inference with Constrained Hidden Markov Models in PRISM |
Abstract: A Hidden Markov Model (HMM) is a common statistical model which is widely used for analysis of biological sequence data and other sequential phenomena. In the present paper we show how HMMs can be extended with side-constraints and present constraint solving techniques for efficient inference. Defining HMMs w... |
Title: An algorithm for the principal component analysis of large data sets |
Abstract: Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy --- even on parallel processors --- unlike the classical (deterministic) alternatives. We adapt one of these randomized methods for use with data sets that are too large to b... |
Title: High-dimensional regression and variable selection using CAR scores |
Abstract: Variable selection is a difficult problem that is particularly challenging in the analysis of high-dimensional genomic data. Here, we introduce the CAR score, a novel and highly effective criterion for variable ranking in linear regression based on Mahalanobis-decorrelation of the explanatory variables. The C... |
Title: Parametric families on large binary spaces |
Abstract: In the context of adaptive Monte Carlo algorithms, we cannot directly generate independent samples from the distribution of interest but use a proxy which we need to be close to the target. Generally, such a proxy distribution is a parametric family on the sampling spaces of the target distribution. For conti... |
Title: Bayesian Model Selection for Beta Autoregressive Processes |
Abstract: We deal with Bayesian inference for Beta autoregressive processes. We restrict our attention to the class of conditionally linear processes. These processes are particularly suitable for forecasting purposes, but are difficult to estimate due to the constraints on the parameter space. We provide a full Bayesi... |
Title: Bayesian Cointegrated Vector Autoregression models incorporating Alpha-stable noise for inter-day price movements via Approximate Bayesian Computation |
Abstract: We consider a statistical model for pairs of traded assets, based on a Cointegrated Vector Auto Regression (CVAR) Model. We extend standard CVAR models to incorporate estimation of model parameters in the presence of price series level shifts which are not accurately modeled in the standard Gaussian error cor... |
Title: Symmetric categorial grammar: residuation and Galois connections |
Abstract: The Lambek-Grishin calculus is a symmetric extension of the Lambek calculus: in addition to the residuated family of product, left and right division operations of Lambek's original calculus, one also considers a family of coproduct, right and left difference operations, related to the former by an arrow-reve... |
Title: Mixture decompositions of exponential families using a decomposition of their sample spaces |
Abstract: We study the problem of finding the smallest $m$ such that every element of an exponential family can be written as a mixture of $m$ elements of another exponential family. We propose an approach based on coverings and packings of the face lattice of the corresponding convex support polytopes and results from... |
Title: Threat assessment of a possible Vehicle-Born Improvised Explosive Device using DSmT |
Abstract: This paper presents the solution about the threat of a VBIED (Vehicle-Born Improvised Explosive Device) obtained with the DSmT (Dezert-Smarandache Theory). This problem has been proposed recently to the authors by Simon Maskell and John Lavery as a typical illustrative example to try to compare the different ... |
Title: Co-evolution is Incompatible with the Markov Assumption in Phylogenetics |
Abstract: Markov models are extensively used in the analysis of molecular evolution. A recent line of research suggests that pairs of proteins with functional and physical interactions co-evolve with each other. Here, by analyzing hundreds of orthologous sets of three fungi and their co-evolutionary relations, we demon... |
Title: Close Clustering Based Automated Color Image Annotation |
Abstract: Most image-search approaches today are based on the text based tags associated with the images which are mostly human generated and are subject to various kinds of errors. The results of a query to the image database thus can often be misleading and may not satisfy the requirements of the user. In this work w... |
Title: Penalized Likelihood Regression in Reproducing Kernel Hilbert Spaces with Randomized Covariate Data |
Abstract: Classical penalized likelihood regression problems deal with the case that the independent variables data are known exactly. In practice, however, it is common to observe data with incomplete covariate information. We are concerned with a fundamentally important case where some of the observations do not repr... |
Title: Fully automatic extraction of salient objects from videos in near real-time |
Abstract: Automatic video segmentation plays an important role in a wide range of computer vision and image processing applications. Recently, various methods have been proposed for this purpose. The problem is that most of these methods are far from real-time processing even for low-resolution videos due to the comple... |
Title: Bounded Coordinate-Descent for Biological Sequence Classification in High Dimensional Predictor Space |
Abstract: We present a framework for discriminative sequence classification where the learner works directly in the high dimensional predictor space of all subsequences in the training set. This is possible by employing a new coordinate-descent algorithm coupled with bounding the magnitude of the gradient for selecting... |
Title: Image sequence interpolation using optimal control |
Abstract: The problem of the generation of an intermediate image between two given images in an image sequence is considered. The problem is formulated as an optimal control problem governed by a transport equation. This approach bears similarities with the Horn \& Schunck method for optical flow calculation but in fac... |
Title: Evaluating and Improving Modern Variable and Revision Ordering Strategies in CSPs |
Abstract: A key factor that can dramatically reduce the search space during constraint solving is the criterion under which the variable to be instantiated next is selected. For this purpose numerous heuristics have been proposed. Some of the best of such heuristics exploit information about failures gathered throughou... |
Title: Adaptive Branching for Constraint Satisfaction Problems |
Abstract: The two standard branching schemes for CSPs are d-way and 2-way branching. Although it has been shown that in theory the latter can be exponentially more effective than the former, there is a lack of empirical evidence showing such differences. To investigate this, we initially make an experimental comparison... |
Title: Algorithmic Detection of Computer Generated Text |
Abstract: Computer generated academic papers have been used to expose a lack of thorough human review at several computer science conferences. We assess the problem of classifying such documents. After identifying and evaluating several quantifiable features of academic papers, we apply methods from machine learning to... |
Title: Systems Theoretic Techniques for Modeling, Control, and Decision Support in Complex Dynamic Systems |
Abstract: We discuss the problems of modeling, control, and decision support in complex dynamic systems from a general system theoretic point of view. The main characteristics of complex systems and of system approach to complex system study are considered. We provide an overview and analysis of known existing paradigm... |
Title: A Homogeneous Reaction Rule Language for Complex Event Processing |
Abstract: Event-driven automation of reactive functionalities for complex event processing is an urgent need in today's distributed service-oriented architectures and Web-based event-driven environments. An important problem to be addressed is how to correctly and efficiently capture and process the event-based behavio... |
Title: Associative control processor with a rigid structure |
Abstract: The approach of applying associative processor for decision making problem was proposed. It focuses on hardware implementations of fuzzy processing systems, associativity as effective management basis of fuzzy processor. The structural approach is being developed resulting in a quite simple and compact parall... |
Title: Modeling the growth of fingerprints improves matching for adolescents |
Abstract: We study the effect of growth on the fingerprints of adolescents, based on which we suggest a simple method to adjust for growth when trying to recover a juvenile's fingerprint in a database years later. Based on longitudinal data sets in juveniles' criminal records, we show that growth essentially leads to a... |
Title: Towards arrow-theoretic semantics of ontologies: conceptories |
Abstract: In context of efforts of composing category-theoretic and logical methods in the area of knowledge representation we propose the notion of conceptory. We consider intersection/union and other constructions in conceptories as expressive alternative to category-theoretic (co)limits and show they have features s... |
Title: Semantic Oriented Agent based Approach towards Engineering Data Management, Web Information Retrieval and User System Communication Problems |
Abstract: The four intensive problems to the software rose by the software industry .i.e., User System Communication / Human Machine Interface, Meta Data extraction, Information processing & management and Data representation are discussed in this research paper. To contribute in the field we have proposed and describe... |
Title: An Agent based Approach towards Metadata Extraction, Modelling and Information Retrieval over the Web |
Abstract: Web development is a challenging research area for its creativity and complexity. The existing raised key challenge in web technology technologic development is the presentation of data in machine read and process able format to take advantage in knowledge based information extraction and maintenance. Current... |
Title: Adaptive post-Dantzig estimation and prediction for non-sparse "large $p$ and small $n$" models |
Abstract: For consistency (even oracle properties) of estimation and model prediction, almost all existing methods of variable/feature selection critically depend on sparsity of models. However, for ``large $p$ and small $n$" models sparsity assumption is hard to check and particularly, when this assumption is violated... |
Title: Control Variates for Reversible MCMC Samplers |
Abstract: A general methodology is introduced for the construction and effective application of control variates to estimation problems involving data from reversible MCMC samplers. We propose the use of a specific class of functions as control variates, and we introduce a new, consistent estimator for the values of th... |
Title: Towards Nonstationary, Nonparametric Independent Process Analysis with Unknown Source Component Dimensions |
Abstract: The goal of this paper is to extend independent subspace analysis (ISA) to the case of (i) nonparametric, not strictly stationary source dynamics and (ii) unknown source component dimensions. We make use of functional autoregressive (fAR) processes to model the temporal evolution of the hidden sources. An ext... |
Title: Towards Design and Implementation of a Language Technology based Information Processor for PDM Systems |
Abstract: Product Data Management (PDM) aims to provide 'Systems' contributing in industries by electronically maintaining organizational data, improving data repository system, facilitating with easy access to CAD and providing additional information engineering and management modules to access, store, integrate, secu... |
Title: Semi-Supervised Kernel PCA |
Abstract: We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points. The first, MV-KPCA, penalises within class variances similar to Fisher discriminant analysis. The second, LSKPCA is a hybrid of least squares regressi... |
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