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Abstract: We introduce a new smooth estimator of the ROC curve based on log-concave density estimates of the constituent distributions. We show that our estimate is asymptotically equivalent to the empirical ROC curve if the underlying densities are in fact log-concave. In addition, we empirically show that our propose... |
Title: Integrated information increases with fitness in the evolution of animats |
Abstract: One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organism... |
Title: Probability boxes on totally preordered spaces for multivariate modelling |
Abstract: A pair of lower and upper cumulative distribution functions, also called probability box or p-box, is among the most popular models used in imprecise probability theory. They arise naturally in expert elicitation, for instance in cases where bounds are specified on the quantiles of a random variable, or when ... |
Title: Recognizing Uncertainty in Speech |
Abstract: We address the problem of inferring a speaker's level of certainty based on prosodic information in the speech signal, which has application in speech-based dialogue systems. We show that using phrase-level prosodic features centered around the phrases causing uncertainty, in addition to utterance-level proso... |
Title: Ray-Based and Graph-Based Methods for Fiber Bundle Boundary Estimation |
Abstract: Diffusion Tensor Imaging (DTI) provides the possibility of estimating the location and course of eloquent structures in the human brain. Knowledge about this is of high importance for preoperative planning of neurosurgical interventions and for intraoperative guidance by neuronavigation in order to minimize p... |
Title: Nonparametric Methodology for the Time-Dependent Partial Area under the ROC Curve |
Abstract: To assess the classification accuracy of a continuous diagnostic result, the receiver operating characteristic (ROC) curve is commonly used in applications. The partial area under the ROC curve (pAUC) is one of widely accepted summary measures due to its generality and ease of probability interpretation. In t... |
Title: COMET: A Recipe for Learning and Using Large Ensembles on Massive Data |
Abstract: COMET is a single-pass MapReduce algorithm for learning on large-scale data. It builds multiple random forest ensembles on distributed blocks of data and merges them into a mega-ensemble. This approach is appropriate when learning from massive-scale data that is too large to fit on a single machine. To get th... |
Title: An Artificial Immune System Model for Multi-Agents Resource Sharing in Distributed Environments |
Abstract: Natural Immune system plays a vital role in the survival of the all living being. It provides a mechanism to defend itself from external predates making it consistent systems, capable of adapting itself for survival incase of changes. The human immune system has motivated scientists and engineers for finding ... |
Title: A hybrid model for bankruptcy prediction using genetic algorithm, fuzzy c-means and mars |
Abstract: Bankruptcy prediction is very important for all the organization since it affects the economy and rise many social problems with high costs. There are large number of techniques have been developed to predict the bankruptcy, which helps the decision makers such as investors and financial analysts. One of the ... |
Title: Self reference in word definitions |
Abstract: Dictionaries are inherently circular in nature. A given word is linked to a set of alternative words (the definition) which in turn point to further descendants. Iterating through definitions in this way, one typically finds that definitions loop back upon themselves. The graph formed by such definitional rel... |
Title: SPPAM - Statistical PreProcessing AlgorithM |
Abstract: Most machine learning tools work with a single table where each row is an instance and each column is an attribute. Each cell of the table contains an attribute value for an instance. This representation prevents one important form of learning, which is, classification based on groups of correlated records, s... |
Title: Adaptive mosaic image representation for image processing |
Abstract: Method for a mosaic image representation (MIR) is proposed for a selective treatment of image fragments of different transition frequency. MIR method is based on piecewise-constant image approximation on a non-uniform orthogonal grid constructed by the following recurrent multigrid algorithm. A sequence of ne... |
Title: A general class of zero-or-one inflated beta regression models |
Abstract: This paper proposes a general class of regression models for continuous proportions when the data contain zeros or ones. The proposed class of models assumes that the response variable has a mixed continuous-discrete distribution with probability mass at zero or one. The beta distribution is used to describe ... |
Title: Language, Emotions, and Cultures: Emotional Sapir-Whorf Hypothesis |
Abstract: An emotional version of Sapir-Whorf hypothesis suggests that differences in language emotionalities influence differences among cultures no less than conceptual differences. Conceptual contents of languages and cultures to significant extent are determined by words and their semantic differences; these could ... |
Title: Dynamic Retrospective Regression for Functional Data |
Abstract: Samples of curves, or functional data, usually present phase variability in addition to amplitude variability. Existing functional regression methods do not handle phase variability in an efficient way. In this paper we propose a functional regression method that incorporates phase synchronization as an intri... |
Title: Heterogeneous Learning in Zero-Sum Stochastic Games with Incomplete Information |
Abstract: Learning algorithms are essential for the applications of game theory in a networking environment. In dynamic and decentralized settings where the traffic, topology and channel states may vary over time and the communication between agents is impractical, it is important to formulate and study games of incomp... |
Title: Sequences of regressions and their independences |
Abstract: Ordered sequences of univariate or multivariate regressions provide statistical models for analysing data from randomized, possibly sequential interventions, from cohort or multi-wave panel studies, but also from cross-sectional or retrospective studies. Conditional independences are captured by what we name ... |
Title: SO(3)-invariant asymptotic observers for dense depth field estimation based on visual data and known camera motion |
Abstract: In this paper, we use known camera motion associated to a video sequence of a static scene in order to estimate and incrementally refine the surrounding depth field. We exploit the SO(3)-invariance of brightness and depth fields dynamics to customize standard image processing techniques. Inspired by the Horn-... |
Title: Constrained Mixture Models for Asset Returns Modelling |
Abstract: The estimation of asset return distributions is crucial for determining optimal trading strategies. In this paper we describe the constrained mixture model, based on a mixture of Gamma and Gaussian distributions, to provide an accurate description of price trends as being clearly positive, negative or ranging... |
Title: A Paradoxical Property of the Monkey Book |
Abstract: A "monkey book" is a book consisting of a random distribution of letters and blanks, where a group of letters surrounded by two blanks is defined as a word. We compare the statistics of the word distribution for a monkey book with the corresponding distribution for the general class of random books, where the... |
Title: Sparsity with sign-coherent groups of variables via the cooperative-Lasso |
Abstract: We consider the problems of estimation and selection of parameters endowed with a known group structure, when the groups are assumed to be sign-coherent, that is, gathering either nonnegative, nonpositive or null parameters. To tackle this problem, we propose the cooperative-Lasso penalty. We derive the optim... |
Title: Sparse Transfer Learning for Interactive Video Search Reranking |
Abstract: Visual reranking is effective to improve the performance of the text-based video search. However, existing reranking algorithms can only achieve limited improvement because of the well-known semantic gap between low level visual features and high level semantic concepts. In this paper, we adopt interactive vi... |
Title: Universal low-rank matrix recovery from Pauli measurements |
Abstract: We study the problem of reconstructing an unknown matrix M of rank r and dimension d using O(rd poly log d) Pauli measurements. This has applications in quantum state tomography, and is a non-commutative analogue of a well-known problem in compressed sensing: recovering a sparse vector from a few of its Fouri... |
Title: Autotagging music with conditional restricted Boltzmann machines |
Abstract: This paper describes two applications of conditional restricted Boltzmann machines (CRBMs) to the task of autotagging music. The first consists of training a CRBM to predict tags that a user would apply to a clip of a song based on tags already applied by other users. By learning the relationships between tag... |
Title: Interaction patterns of brain activity across space, time and frequency. Part I: methods |
Abstract: We consider exploratory methods for the discovery of cortical functional connectivity. Typically, data for the i-th subject (i=1...NS) is represented as an NVxNT matrix Xi, corresponding to brain activity sampled at NT moments in time from NV cortical voxels. A widely used method of analysis first concatenate... |
Title: Extreme value analysis of actuarial risks: estimation and model validation |
Abstract: We give an overview of several aspects arising in the statistical analysis of extreme risks with actuarial applications in view. In particular it is demonstrated that empirical process theory is a very powerful tool, both for the asymptotic analysis of extreme value estimators and to devise tools for the vali... |
Title: A framework for list representation, enabling list stabilization through incorporation of gene exchangeabilities |
Abstract: Analysis of multivariate data sets from e.g. microarray studies frequently results in lists of genes which are associated with some response of interest. The biological interpretation is often complicated by the statistical instability of the obtained gene lists with respect to sampling variations, which may ... |
Title: A new ANEW: Evaluation of a word list for sentiment analysis in microblogs |
Abstract: Sentiment analysis of microblogs such as Twitter has recently gained a fair amount of attention. One of the simplest sentiment analysis approaches compares the words of a posting against a labeled word list, where each word has been scored for valence, -- a 'sentiment lexicon' or 'affective word lists'. There... |
Title: Fitting Ranked English and Spanish Letter Frequency Distribution in U.S. and Mexican Presidential Speeches |
Abstract: The limited range in its abscissa of ranked letter frequency distributions causes multiple functions to fit the observed distribution reasonably well. In order to critically compare various functions, we apply the statistical model selections on ten functions, using the texts of U.S. and Mexican presidential ... |
Title: Bayesian versus frequentist upper limits |
Abstract: While gravitational waves have not yet been measured directly, data analysis from detection experiments commonly includes an upper limit statement. Such upper limits may be derived via a frequentist or Bayesian approach; the theoretical implications are very different, and on the technical side, one notable d... |
Title: A note on active learning for smooth problems |
Abstract: We show that the disagreement coefficient of certain smooth hypothesis classes is $O(m)$, where $m$ is the dimension of the hypothesis space, thereby answering a question posed in . |
Title: Reduced Ordered Binary Decision Diagram with Implied Literals: A New knowledge Compilation Approach |
Abstract: Knowledge compilation is an approach to tackle the computational intractability of general reasoning problems. According to this approach, knowledge bases are converted off-line into a target compilation language which is tractable for on-line querying. Reduced ordered binary decision diagram (ROBDD) is one o... |
Title: Using Soft Computer Techniques on Smart Devices for Monitoring Chronic Diseases: the CHRONIOUS case |
Abstract: CHRONIOUS is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote senso... |
Title: Multi-parameter acoustic imaging of uniform objects in inhomogeneous media |
Abstract: The problem studied in this paper is ultrasound image reconstruction from frequency-domain measurements of the scattered field from an object with contrast in attenuation and sound speed. The case where the object has uniform but unknown contrast in these properties relative to the background is considered. B... |
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