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We improve the main result of Brody and Verbin [7] from FOCS 2010 on the power of constant-width branching programs to distinguish product distributions. Specifically, we show that a coin must have bi...
We study the problem of learning from unlabeled samples very general statistical mixture models on large finite sets.Specifically, the model to be learned, ϑ, is a probability dis-tribution over ...
We develop a general theory of reaction time ({RT}) distributions in psychological experiments, deriving from the distribution of the quotient of two normal random variables, that of the task difficul...
This paper analyzes the convergence properties of an iterative Monte Carlo procedure proposed in the Physics literature for estimating the quasi-stationary distribution on a transient set of a Markov ...
Image priors based on products have been recognized to offer many advantages because they allow simultaneous enforcement of multiple constraints. However, they are inconvenient for Bayesian inferenc...
The 3D integration of dies promises to address the problem of increased die size caused by the slowing of scaling. By partitioning a design among two or more dies and stacking them vertically, the ave...
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...
The multivariate Student $t$ distribution is at the core of classical statistical inference and is also a well-known model for empirical financial data. In the present paper, we propose optimal (in th...
For multivariate continuous data, the contaminated Gaussian distribution - having two parameters indicating the proportion of outliers and the degree of contamination - represents a convenient and nat...
We introduce a mixture of generalized hyperbolic distributions as an alternative to the ubiquitous mixture of Gaussian distributions as well as their near relatives of which the mixture of multivariat...
In astrophysics a common goal is to infer the flux distribution of populations of scientifically interesting objects such as pulsars or supernovae. In practice, inference for the flux distribution is ...
One-sample and multi-sample tests on the concentration parameter of Fisher-von Mises-Langevin (FvML) distributions have been well studied in the literature. However, only very little is known about th...
Assessing variability according to distinct factors in data is a fundamental technique of statistics. The method commonly regarded to as analysis of variance (ANOVA) is, however, typically confined to...
We study the problem of learning Markov decision processes with finite state and action spaces when the transition probability distributions and loss functions are chosen adversarially and are allowed...
A new classifier for Polarimetric SAR (PolSAR) images is proposed and assessed in this paper. Its input consists of segments, and each one is assigned the class which minimizes a stochastic distance. ...

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