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Abstract: Although some information-theoretic measures of uncertainty or granularity have been proposed in rough set theory, these measures are only dependent on the underlying partition and the cardinality of the universe, independent of the lower and upper approximations. It seems somewhat unreasonable since the basi... |
Title: High-Performance Neural Networks for Visual Object Classification |
Abstract: We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants. Our feature extractors are neither carefully designed nor pre-wired, but rather learned in a supervised way. Our deep hierarchical architectures achieve the best published results on benchmarks for object cla... |
Title: Speeding up SAT solver by exploring CNF symmetries : Revisited |
Abstract: Boolean Satisfiability solvers have gone through dramatic improvements in their performances and scalability over the last few years by considering symmetries. It has been shown that by using graph symmetries and generating symmetry breaking predicates (SBPs) it is possible to break symmetries in Conjunctive ... |
Title: Emergence through Selection: The Evolution of a Scientific Challenge |
Abstract: One of the most interesting scientific challenges nowadays deals with the analysis and the understanding of complex networks' dynamics and how their processes lead to emergence according to the interactions among their components. In this paper we approach the definition of new methodologies for the visualiza... |
Title: Fisher information matrix for three-parameter exponentiated-Weibull distribution under type II censoring |
Abstract: This paper considers the three-parameter exponentiated Weibull family under type II censoring. It first graphically illustrates the shape property of the hazard function. Then, it proposes a simple algorithm for computing the maximum likelihood estimator and derives the Fisher information matrix. The latter o... |
Title: Asymptotically optimal parameter estimation under communication constraints |
Abstract: A parameter estimation problem is considered, in which dispersed sensors transmit to the statistician partial information regarding their observations. The sensors observe the paths of continuous semimartingales, whose drifts are linear with respect to a common parameter. A novel estimating scheme is suggeste... |
Title: Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot |
Abstract: This paper addresses object perception applied to mobile robotics. Being able to perceive semantically meaningful objects in unstructured environments is a key capability in order to make robots suitable to perform high-level tasks in home environments. However, finding a solution for this task is daunting: i... |
Title: Delays Induce an Exponential Memory Gap for Rendezvous in Trees |
Abstract: The aim of rendezvous in a graph is meeting of two mobile agents at some node of an unknown anonymous connected graph. In this paper, we focus on rendezvous in trees, and, analogously to the efforts that have been made for solving the exploration problem with compact automata, we study the size of memory of m... |
Title: A study of variable selection using g-prior distribution with ridge parameter |
Abstract: In the Bayesian stochastic search variable selection framework, a common prior distribution for the regression coefficients is the g-prior of Zellner (1986). However, there are two standard cases in which the associated covariance matrix does not exist, and the conventional prior of Zellner can not be used: i... |
Title: Optimal sequential change-detection for fractional diffusion-type processes |
Abstract: We consider the problem of detecting an abrupt change in the distribution of a sequentially observed stochastic process. We establish the optimality of the CUSUM test with respect to a modified version of Lorden's criterion for arbitrary processes with continuous paths and apply this general result to the spe... |
Title: Persistent Robotic Tasks: Monitoring and Sweeping in Changing Environments |
Abstract: We present controllers that enable mobile robots to persistently monitor or sweep a changing environment. The changing environment is modeled as a field which grows in locations that are not within range of a robot, and decreases in locations that are within range of a robot. We assume that the robots travel ... |
Title: Time-Varying Graphs and Social Network Analysis: Temporal Indicators and Metrics |
Abstract: Most instruments - formalisms, concepts, and metrics - for social networks analysis fail to capture their dynamics. Typical systems exhibit different scales of dynamics, ranging from the fine-grain dynamics of interactions (which recently led researchers to consider temporal versions of distance, connectivity... |
Title: An architecture for the evaluation of intelligent systems |
Abstract: One of the main research areas in Artificial Intelligence is the coding of agents (programs) which are able to learn by themselves in any situation. This means that agents must be useful for purposes other than those they were created for, as, for example, playing chess. In this way we try to get closer to th... |
Title: Natural images from the birthplace of the human eye |
Abstract: Here we introduce a database of calibrated natural images publicly available through an easy-to-use web interface. Using a Nikon D70 digital SLR camera, we acquired about 5000 six-megapixel images of Okavango Delta of Botswana, a tropical savanna habitat similar to where the human eye is thought to have evolv... |
Title: Intelligent Semantic Web Search Engines: A Brief Survey |
Abstract: The World Wide Web (WWW) allows the people to share the information (data) from the large database repositories globally. The amount of information grows billions of databases. We need to search the information will specialize tools known generically search engine. There are many of search engines available t... |
Title: EigenNet: A Bayesian hybrid of generative and conditional models for sparse learning |
Abstract: It is a challenging task to select correlated variables in a high dimensional space. To address this challenge, the elastic net has been developed and successfully applied to many applications. Despite its great success, the elastic net does not explicitly use correlation information embedded in data to selec... |
Title: A convex model for non-negative matrix factorization and dimensionality reduction on physical space |
Abstract: A collaborative convex framework for factoring a data matrix $X$ into a non-negative product $AS$, with a sparse coefficient matrix $S$, is proposed. We restrict the columns of the dictionary matrix $A$ to coincide with certain columns of the data matrix $X$, thereby guaranteeing a physically meaningful dicti... |
Title: Evidence Feed Forward Hidden Markov Model: A New Type of Hidden Markov Model |
Abstract: The ability to predict the intentions of people based solely on their visual actions is a skill only performed by humans and animals. The intelligence of current computer algorithms has not reached this level of complexity, but there are several research efforts that are working towards it. With the number of... |
Title: Outliers and patterns of outliers in contingency tables with Algebraic Statistics |
Abstract: In this paper we provide a definition of pattern of outliers in contingency tables within a model-based framework. In particular, we make use of log-linear models and exact goodness-of-fit tests to specify the notions of outlier and pattern of outliers. The language and some techniques from Algebraic Statisti... |
Title: On statistical uncertainty in nested sampling |
Abstract: Nested sampling has emerged as a valuable tool for Bayesian analysis, in particular for determining the Bayesian evidence. The method is based on a specific type of random sampling of the likelihood function and prior volume of the parameter space. I study the statistical uncertainty in the evidence computed ... |
Title: Collective Classification of Textual Documents by Guided Self-Organization in T-Cell Cross-Regulation Dynamics |
Abstract: We present and study an agent-based model of T-Cell cross-regulation in the adaptive immune system, which we apply to binary classification. Our method expands an existing analytical model of T-cell cross-regulation (Carneiro et al. in Immunol Rev 216(1):48-68, 2007) that was used to study the self-organizing... |
Title: Total variation regularization for fMRI-based prediction of behaviour |
Abstract: While medical imaging typically provides massive amounts of data, the extraction of relevant information for predictive diagnosis remains a difficult challenge. Functional MRI (fMRI) data, that provide an indirect measure of task-related or spontaneous neuronal activity, are classically analyzed in a mass-uni... |
Title: Phase transition in the detection of modules in sparse networks |
Abstract: We present an asymptotically exact analysis of the problem of detecting communities in sparse random networks. Our results are also applicable to detection of functional modules, partitions, and colorings in noisy planted models. Using a cavity method analysis, we unveil a phase transition from a region where... |
Title: Smoothed log-concave maximum likelihood estimation with applications |
Abstract: We study the smoothed log-concave maximum likelihood estimator of a probability distribution on $^d$. This is a fully automatic nonparametric density estimator, obtained as a canonical smoothing of the log-concave maximum likelihood estimator. We demonstrate its attractive features both through an analysis of... |
Title: Large Scale Correlation Screening |
Abstract: This paper treats the problem of screening for variables with high correlations in high dimensional data in which there can be many fewer samples than variables. We focus on threshold-based correlation screening methods for three related applications: screening for variables with large correlations within a s... |
Title: Modeling Dynamic Swarms |
Abstract: This paper proposes the problem of modeling video sequences of dynamic swarms (DS). We define DS as a large layout of stochastically repetitive spatial configurations of dynamic objects (swarm elements) whose motions exhibit local spatiotemporal interdependency and stationarity, i.e., the motions are similar ... |
Title: Refinement of Operator-valued Reproducing Kernels |
Abstract: This paper studies the construction of a refinement kernel for a given operator-valued reproducing kernel such that the vector-valued reproducing kernel Hilbert space of the refinement kernel contains that of the given one as a subspace. The study is motivated from the need of updating the current operator-va... |
Title: An Introduction to Artificial Prediction Markets for Classification |
Abstract: Prediction markets are used in real life to predict outcomes of interest such as presidential elections. This paper presents a mathematical theory of artificial prediction markets for supervised learning of conditional probability estimators. The artificial prediction market is a novel method for fusing the p... |
Title: On Nonparametric Guidance for Learning Autoencoder Representations |
Abstract: Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for learning features relevant to discriminative tasks. Autoencoders, in particular, have proven to be an effective way to learn laten... |
Title: Evolutionary multiobjective optimization of the multi-location transshipment problem |
Abstract: We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However, this transshipment process usually causes... |
Title: Schema Redescription in Cellular Automata: Revisiting Emergence in Complex Systems |
Abstract: We present a method to eliminate redundancy in the transition tables of Boolean automata: schema redescription with two symbols. One symbol is used to capture redundancy of individual input variables, and another to capture permutability in sets of input variables: fully characterizing the canalization presen... |
Title: Restructuring in Combinatorial Optimization |
Abstract: The paper addresses a new class of combinatorial problems which consist in restructuring of solutions (as structures) in combinatorial optimization. Two main features of the restructuring process are examined: (i) a cost of the restructuring, (ii) a closeness to a goal solution. This problem corresponds to re... |
Title: Graph Coalition Structure Generation |
Abstract: We give the first analysis of the computational complexity of \it coalition structure generation over graphs. Given an undirected graph $G=(N,E)$ and a valuation function $v:2^N\rightarrow\RR$ over the subsets of nodes, the problem is to find a partition of $N$ into connected subsets, that maximises the sum o... |
Title: Predictors of short-term decay of cell phone contacts in a large scale communication network |
Abstract: Under what conditions is an edge present in a social network at time t likely to decay or persist by some future time t + Delta(t)? Previous research addressing this issue suggests that the network range of the people involved in the edge, the extent to which the edge is embedded in a surrounding structure, a... |
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