text stringlengths 0 4.09k |
|---|
Abstract: The objective of this paper is to develop statistical methodology for planning and evaluating three-armed non-inferiority trials for general retention of effect hypotheses, where the endpoint of interest may follow any (regular) parametric distribution family. This generalizes and unifies specific results for... |
Title: Test Martingales, Bayes Factors and $p$-Values |
Abstract: A nonnegative martingale with initial value equal to one measures evidence against a probabilistic hypothesis. The inverse of its value at some stopping time can be interpreted as a Bayes factor. If we exaggerate the evidence by considering the largest value attained so far by such a martingale, the exaggerat... |
Title: Inferring Multiple Graphical Structures |
Abstract: Gaussian Graphical Models provide a convenient framework for representing dependencies between variables. Recently, this tool has received a high interest for the discovery of biological networks. The literature focuses on the case where a single network is inferred from a set of measurements, but, as wetlab ... |
Title: Learning to Predict Combinatorial Structures |
Abstract: The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. ... |
Title: Consensus Dynamics in a non-deterministic Naming Game with Shared Memory |
Abstract: In the naming game, individuals or agents exchange pairwise local information in order to communicate about objects in their common environment. The goal of the game is to reach a consensus about naming these objects. Originally used to investigate language formation and self-organizing vocabularies, we exten... |
Title: Lambert W random variables - a new family of generalized skewed distributions with applications to risk estimation |
Abstract: Originating from a system theory and an input/output point of view, I introduce a new class of generalized distributions. A parametric nonlinear transformation converts a random variable $X$ into a so-called Lambert $W$ random variable $Y$, which allows a very flexible approach to model skewed data. Its shape... |
Title: Fast Alternating Linearization Methods for Minimizing the Sum of Two Convex Functions |
Abstract: We present in this paper first-order alternating linearization algorithms based on an alternating direction augmented Lagrangian approach for minimizing the sum of two convex functions. Our basic methods require at most $O(1/\epsilon)$ iterations to obtain an $\epsilon$-optimal solution, while our accelerated... |
Title: A Necessary and Sufficient Condition for Graph Matching Being Equivalent to the Maximum Weight Clique Problem |
Abstract: This paper formulates a necessary and sufficient condition for a generic graph matching problem to be equivalent to the maximum vertex and edge weight clique problem in a derived association graph. The consequences of this results are threefold: first, the condition is general enough to cover a broad range of... |
Title: Elkan's k-Means for Graphs |
Abstract: This paper extends k-means algorithms from the Euclidean domain to the domain of graphs. To recompute the centroids, we apply subgradient methods for solving the optimization-based formulation of the sample mean of graphs. To accelerate the k-means algorithm for graphs without trading computational time again... |
Title: The use of ideas of Information Theory for studying "language" and intelligence in ants |
Abstract: In this review we integrate results of long term experimental study on ant "language" and intelligence which were fully based on fundamental ideas of Information Theory, such as the Shannon entropy, the Kolmogorov complexity, and the Shannon's equation connecting the length of a message ($l$) and its frequenc... |
Title: Likelihood-free Bayesian inference for alpha-stable models |
Abstract: $\alpha$-stable distributions are utilised as models for heavy-tailed noise in many areas of statistics, finance and signal processing engineering. However, in general, neither univariate nor multivariate $\alpha$-stable models admit closed form densities which can be evaluated pointwise. This complicates the... |
Title: Similarit\'e en intension vs en extension : \`a la crois\'ee de l'informatique et du th\'e\^atre |
Abstract: Traditional staging is based on a formal approach of similarity leaning on dramaturgical ontologies and instanciation variations. Inspired by interactive data mining, that suggests different approaches, we give an overview of computer science and theater researches using computers as partners of the actor to ... |
Title: On Finding Predictors for Arbitrary Families of Processes |
Abstract: The problem is sequence prediction in the following setting. A sequence $x_1,...,x_n,...$ of discrete-valued observations is generated according to some unknown probabilistic law (measure) $\mu$. After observing each outcome, it is required to give the conditional probabilities of the next observation. The me... |
Title: An Invariance Principle for Polytopes |
Abstract: Let X be randomly chosen from -1,1^n, and let Y be randomly chosen from the standard spherical Gaussian on R^n. For any (possibly unbounded) polytope P formed by the intersection of k halfspaces, we prove that |Pr [X belongs to P] - Pr [Y belongs to P]| < log^8/5k * Delta, where Delta is a parameter that is s... |
Title: Nonparametric Bayesian Density Modeling with Gaussian Processes |
Abstract: We present the Gaussian process density sampler (GPDS), an exchangeable generative model for use in nonparametric Bayesian density estimation. Samples drawn from the GPDS are consistent with exact, independent samples from a distribution defined by a density that is a transformation of a function drawn from a... |
Title: Genus Computing for 3D digital objects: algorithm and implementation |
Abstract: This paper deals with computing topological invariants such as connected components, boundary surface genus, and homology groups. For each input data set, we have designed or implemented algorithms to calculate connected components, boundary surfaces and their genus, and homology groups. Due to the fact that ... |
Title: Inference for Extremal Conditional Quantile Models, with an Application to Market and Birthweight Risks |
Abstract: Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many economic and financia... |
Title: Complexity of stochastic branch and bound methods for belief tree search in Bayesian reinforcement learning |
Abstract: There has been a lot of recent work on Bayesian methods for reinforcement learning exhibiting near-optimal online performance. The main obstacle facing such methods is that in most problems of interest, the optimal solution involves planning in an infinitely large tree. However, it is possible to obtain stoch... |
Title: A Rational Decision Maker with Ordinal Utility under Uncertainty: Optimism and Pessimism |
Abstract: In game theory and artificial intelligence, decision making models often involve maximizing expected utility, which does not respect ordinal invariance. In this paper, the author discusses the possibility of preserving ordinal invariance and still making a rational decision under uncertainty. |
Title: Ranking relations using analogies in biological and information networks |
Abstract: Analogical reasoning depends fundamentally on the ability to learn and generalize about relations between objects. We develop an approach to relational learning which, given a set of pairs of objects $=\A^(1):B^(1),A^(2):B^(2),\ldots,A^(N):B ^(N)\$, measures how well other pairs A:B fit in with the set $$. Ou... |
Title: Penalized Composite Quasi-Likelihood for Ultrahigh-Dimensional Variable Selection |
Abstract: In high-dimensional model selection problems, penalized simple least-square approaches have been extensively used. This paper addresses the question of both robustness and efficiency of penalized model selection methods, and proposes a data-driven weighted linear combination of convex loss functions, together... |
Title: Believe It or Not: Adding Belief Annotations to Databases |
Abstract: We propose a database model that allows users to annotate data with belief statements. Our motivation comes from scientific database applications where a community of users is working together to assemble, revise, and curate a shared data repository. As the community accumulates knowledge and the database con... |
Title: Selection models under generalized symmetry settings |
Abstract: An active stream of literature has followed up the idea of skew-elliptical densities initiated by Azzalini and Capitanio (1999). Their original formulation was based on a general lemma which is however of broader applicability than usually perceived. This note examines new directions of its use, and illustrat... |
Title: Why so? or Why no? Functional Causality for Explaining Query Answers |
Abstract: In this paper, we propose causality as a unified framework to explain query answers and non-answers, thus generalizing and extending several previously proposed approaches of provenance and missing query result explanations. We develop our framework starting from the well-studied definition of actual causes b... |
Title: A survey of statistical network models |
Abstract: Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on ... |
Title: Computing Optimal Designs of multiresponse Experiments reduces to Second-Order Cone Programming |
Abstract: Elfving's Theorem is a major result in the theory of optimal experimental design, which gives a geometrical characterization of $c-$optimality. In this paper, we extend this theorem to the case of multiresponse experiments, and we show that when the number of experiments is finite, $c-,A-,T-$ and $D-$optimal ... |
Title: On multivariate quantiles under partial orders |
Abstract: This paper focuses on generalizing quantiles from the ordering point of view. We propose the concept of partial quantiles, which are based on a given partial order. We establish that partial quantiles are equivariant under order-preserving transformations of the data, robust to outliers, characterize the prob... |
Title: Writer Identification Using Inexpensive Signal Processing Techniques |
Abstract: We propose to use novel and classical audio and text signal-processing and otherwise techniques for "inexpensive" fast writer identification tasks of scanned hand-written documents "visually". The "inexpensive" refers to the efficiency of the identification process in terms of CPU cycles while preserving dece... |
Title: MedLDA: A General Framework of Maximum Margin Supervised Topic Models |
Abstract: Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents. Existing models apply the likelihood-based estimation. In this paper, we present a general framework of max-margin supervised topic models for both continuous and categorical re... |
Title: A general approach to belief change in answer set programming |
Abstract: We address the problem of belief change in (nonmonotonic) logic programming under answer set semantics. Unlike previous approaches to belief change in logic programming, our formal techniques are analogous to those of distance-based belief revision in propositional logic. In developing our results, we build u... |
Title: Oriented Straight Line Segment Algebra: Qualitative Spatial Reasoning about Oriented Objects |
Abstract: Nearly 15 years ago, a set of qualitative spatial relations between oriented straight line segments (dipoles) was suggested by Schlieder. This work received substantial interest amongst the qualitative spatial reasoning community. However, it turned out to be difficult to establish a sound constraint calculus... |
Title: The Computational Structure of Spike Trains |
Abstract: Neurons perform computations, and convey the results of those computations through the statistical structure of their output spike trains. Here we present a practical method, grounded in the information-theoretic analysis of prediction, for inferring a minimal representation of that structure and for characte... |
Title: Cryptographic Implications for Artificially Mediated Games |
Abstract: There is currently an intersection in the research of game theory and cryptography. Generally speaking, there are two aspects to this partnership. First there is the application of game theory to cryptography. Yet, the purpose of this paper is to focus on the second aspect, the converse of the first, the appl... |
Title: On a Model for Integrated Information |
Abstract: In this paper we give a thorough presentation of a model proposed by Tononi et al. for modeling , i.e. how much information is generated in a system transitioning from one state to the next one by the causal interaction of its parts and the information given by the sum of its parts. We also provides a more ge... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.