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Abstract: Art historians and archaeologists have long grappled with the regional classification of ancient Near Eastern ivory carvings. Based on the visual similarity of sculptures, individuals within these fields have proposed object assemblages linked to hypothesized regional production centers. Using quantitative ra... |
Title: An Algebraic Approach for the MIMO Control of Small Scale Helicopter |
Abstract: The control of small-scale helicopter is a MIMO problem. To use of classical control approach to formally solve a MIMO problem, one needs to come up with multidimensional Root Locus diagram to tune the control parameters. The problem with the required dimension of the RL diagram for MIMO design has forced the... |
Title: A Fixed-Parameter Algorithm for Random Instances of Weighted d-CNF Satisfiability |
Abstract: We study random instances of the weighted $d$-CNF satisfiability problem (WEIGHTED $d$-SAT), a generic W[1]-complete problem. A random instance of the problem consists of a fixed parameter $k$ and a random $d$-CNF formula $pk, d$ generated as follows: for each subset of $d$ variables and with probability $p$,... |
Title: Sparse Online Learning via Truncated Gradient |
Abstract: We propose a general method called truncated gradient to induce sparsity in the weights of online learning algorithms with convex loss functions. This method has several essential properties: The degree of sparsity is continuous -- a parameter controls the rate of sparsification from no sparsification to tota... |
Title: Improving Point and Interval Estimates of Monotone Functions by Rearrangement |
Abstract: Suppose that a target function is monotonic, namely, weakly increasing, and an available original estimate of this target function is not weakly increasing. Rearrangements, univariate and multivariate, transform the original estimate to a monotonic estimate that always lies closer in common metrics to the tar... |
Title: A new Hedging algorithm and its application to inferring latent random variables |
Abstract: We present a new online learning algorithm for cumulative discounted gain. This learning algorithm does not use exponential weights on the experts. Instead, it uses a weighting scheme that depends on the regret of the master algorithm relative to the experts. In particular, experts whose discounted cumulative... |
Title: Frequentist and Bayesian measures of confidence via multiscale bootstrap for testing three regions |
Abstract: A new computation method of frequentist $p$-values and Bayesian posterior probabilities based on the bootstrap probability is discussed for the multivariate normal model with unknown expectation parameter vector. The null hypothesis is represented as an arbitrary-shaped region. We introduce new parametric mod... |
Title: Graph Kernels |
Abstract: We present a unified framework to study graph kernels, special cases of which include the random walk graph kernel , marginalized graph kernel , and geometric kernel on graphs . Through extensions of linear algebra to Reproducing Kernel Hilbert Spaces (RKHS) and reduction to a Sylvester equation, we construct... |
Title: About the creation of a parallel bilingual corpora of web-publications |
Abstract: The algorithm of the creation texts parallel corpora was presented. The algorithm is based on the use of "key words" in text documents, and on the means of their automated translation. Key words were singled out by means of using Russian and Ukrainian morphological dictionaries, as well as dictionaries of the... |
Title: Unveiling the mystery of visual information processing in human brain |
Abstract: It is generally accepted that human vision is an extremely powerful information processing system that facilitates our interaction with the surrounding world. However, despite extended and extensive research efforts, which encompass many exploration fields, the underlying fundamentals and operational principl... |
Title: Modeling belief systems with scale-free networks |
Abstract: Evolution of belief systems has always been in focus of cognitive research. In this paper we delineate a new model describing belief systems as a network of statements considered true. Testing the model a small number of parameters enabled us to reproduce a variety of well-known mechanisms ranging from opinio... |
Title: Music, Complexity, Information |
Abstract: These are the preparatory notes for a Science & Music essay, "Playing by numbers", appeared in Nature 453 (2008) 988-989. |
Title: Belief decision support and reject for textured images characterization |
Abstract: The textured images' classification assumes to consider the images in terms of area with the same texture. In uncertain environment, it could be better to take an imprecise decision or to reject the area corresponding to an unlearning class. Moreover, on the areas that are the classification units, we can hav... |
Title: Case-deletion importance sampling estimators: Central limit theorems and related results |
Abstract: Case-deleted analysis is a popular method for evaluating the influence of a subset of cases on inference. The use of Monte Carlo estimation strategies in complicated Bayesian settings leads naturally to the use of importance sampling techniques to assess the divergence between full-data and case-deleted poste... |
Title: The Correspondence Analysis Platform for Uncovering Deep Structure in Data and Information |
Abstract: We study two aspects of information semantics: (i) the collection of all relationships, (ii) tracking and spotting anomaly and change. The first is implemented by endowing all relevant information spaces with a Euclidean metric in a common projected space. The second is modelled by an induced ultrametric. A v... |
Title: Bayesian Analysis of Marginal Log-Linear Graphical Models for Three Way Contingency Tables |
Abstract: This paper deals with the Bayesian analysis of graphical models of marginal independence for three way contingency tables. We use a marginal log-linear parametrization, under which the model is defined through suitable zero-constraints on the interaction parameters calculated within marginal distributions. We... |
Title: Catching Up Faster by Switching Sooner: A Prequential Solution to the AIC-BIC Dilemma |
Abstract: Bayesian model averaging, model selection and its approximations such as BIC are generally statistically consistent, but sometimes achieve slower rates og convergence than other methods such as AIC and leave-one-out cross-validation. On the other hand, these other methods can br inconsistent. We identify the ... |
Title: Principal components analysis for sparsely observed correlated functional data using a kernel smoothing approach |
Abstract: In this paper, we consider the problem of estimating the covariance kernel and its eigenvalues and eigenfunctions from sparse, irregularly observed, noise corrupted and (possibly) correlated functional data. We present a method based on pre-smoothing of individual sample curves through an appropriate kernel. ... |
Title: Quantitative comparisons between finitary posterior distributions and Bayesian posterior distributions |
Abstract: The main object of Bayesian statistical inference is the determination of posterior distributions. Sometimes these laws are given for quantities devoid of empirical value. This serious drawback vanishes when one confines oneself to considering a finite horizon framework. However, assuming infinite exchangeabi... |
Title: Semiparametric curve alignment and shift density estimation for biological data |
Abstract: Assume that we observe a large number of curves, all of them with identical, although unknown, shape, but with a different random shift. The objective is to estimate the individual time shifts and their distribution. Such an objective appears in several biological applications like neuroscience or ECG signal ... |
Title: Algorithm Selection as a Bandit Problem with Unbounded Losses |
Abstract: Algorithm selection is typically based on models of algorithm performance, learned during a separate offline training sequence, which can be prohibitively expensive. In recent work, we adopted an online approach, in which a performance model is iteratively updated and used to guide selection on a sequence of ... |
Title: Scientific Paper Summarization Using Citation Summary Networks |
Abstract: Quickly moving to a new area of research is painful for researchers due to the vast amount of scientific literature in each field of study. One possible way to overcome this problem is to summarize a scientific topic. In this paper, we propose a model of summarizing a single article, which can be further used... |
Title: Large-Sample Confidence Intervals for the Treatment Difference in a Two-Period Crossover Trial, Utilizing Prior Information |
Abstract: Consider a two-treatment, two-period crossover trial, with responses that are continuous random variables. We find a large-sample frequentist 1-alpha confidence interval for the treatment difference that utilizes the uncertain prior information that there is no differential carryover effect. |
Title: Extension of Inagaki General Weighted Operators and A New Fusion Rule Class of Proportional Redistribution of Intersection Masses |
Abstract: In this paper we extend Inagaki Weighted Operators fusion rule (WO) in information fusion by doing redistribution of not only the conflicting mass, but also of masses of non-empty intersections, that we call Double Weighted Operators (DWO). Then we propose a new fusion rule Class of Proportional Redistributio... |
Title: Multi-Instance Learning by Treating Instances As Non-I.I.D. Samples |
Abstract: Multi-instance learning attempts to learn from a training set consisting of labeled bags each containing many unlabeled instances. Previous studies typically treat the instances in the bags as independently and identically distributed. However, the instances in a bag are rarely independent, and therefore a be... |
Title: Intrusion Detection Using Cost-Sensitive Classification |
Abstract: Intrusion Detection is an invaluable part of computer networks defense. An important consideration is the fact that raising false alarms carries a significantly lower cost than not detecting at- tacks. For this reason, we examine how cost-sensitive classification methods can be used in Intrusion Detection sys... |
Title: The Five Points Pose Problem : A New and Accurate Solution Adapted to any Geometric Configuration |
Abstract: The goal of this paper is to estimate directly the rotation and translation between two stereoscopic images with the help of five homologous points. The methodology presented does not mix the rotation and translation parameters, which is comparably an important advantage over the methods using the well-known ... |
Title: Two Dimensional Density Estimation using Smooth Invertible Transformations |
Abstract: We investigate the problem of estimating a smooth invertible transformation f when observing independent samples X_1, ..., X_n P \circ f, where P is a known measure. We focus on the two dimensional case where P and f are defined on R^2. We present a flexible class of smooth invertible transformations in two... |
Title: Hardware/Software Co-Design for Spike Based Recognition |
Abstract: The practical applications based on recurrent spiking neurons are limited due to their non-trivial learning algorithms. The temporal nature of spiking neurons is more favorable for hardware implementation where signals can be represented in binary form and communication can be done through the use of spikes. ... |
Title: Polygon Exploration with Time-Discrete Vision |
Abstract: With the advent of autonomous robots with two- and three-dimensional scanning capabilities, classical visibility-based exploration methods from computational geometry have gained in practical importance. However, real-life laser scanning of useful accuracy does not allow the robot to scan continuously while i... |
Title: CPBVP: A Constraint-Programming Framework for Bounded Program Verification |
Abstract: This paper studies how to verify the conformity of a program with its specification and proposes a novel constraint-programming framework for bounded program verification (CPBPV). The CPBPV framework uses constraint stores to represent the specification and the program and explores execution paths nondetermin... |
Title: Text Data Mining: Theory and Methods |
Abstract: This paper provides the reader with a very brief introduction to some of the theory and methods of text data mining. The intent of this article is to introduce the reader to some of the current methodologies that are employed within this discipline area while at the same time making the reader aware of some o... |
Title: A decomposition result for the Haar distribution on the orthogonal group |
Abstract: Let H be a Haar distributed random matrix on the group of pxp real orthogonal matrices. Partition H into four blocks: (1) the (1,1) element, (2)the rest of the first row, (3) the rest of the first column, and (4)the remaining (p-1)x(p-1) matrix. The marginal distribution of (1) is well known. In this paper, w... |
Title: On Endogenous Reconfiguration in Mobile Robotic Networks |
Abstract: In this paper, our focus is on certain applications for mobile robotic networks, where reconfiguration is driven by factors intrinsic to the network rather than changes in the external environment. In particular, we study a version of the coverage problem useful for surveillance applications, where the object... |
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