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We propose a novel general algorithm LHAC that efficiently uses second-order information to train a class of large-scale l1-regularized problems. Our method executes cheap iterations while achieving f...
Non-convex sparsity-inducing penalties have recently received considerable attentions in sparse learning. Recent theoretical investigations have demonstrated their superiority over the convex counterp...
In this paper, we consider unsupervised partitioning problems, such as clustering, image segmentation, video segmentation and other change-point detection problems. We focus on partitioning problems b...
A brief presentation of basics of the theory of Tchebycheff and Markov systems of functions and its applications to extremal problems for integrals of such functions is given.
We consider a Kullback-Leibler-based algorithmfor the stochastic multi-armed bandit prob- lem in the case of distributions with finite supports (not necessarily known beforehand), whose asymptotic r...
We consider the inverse problem of estimating a function u from noisy, possibly nonlinear, observations. We adopt a Bayesian approach to the problem and widen the existing theory, which is developed...
A number of regularization methods for discrete inverse problems consist in considering weighted versions of the usual least square solution. However, these so-called filter methods are generally res...
In applications throughout science and engineering one is often faced with the challenge of solving an ill-posed inverse problem, where the number of available measurements is smaller than the dimensi...
The multiple disorder problem seeks to determine a sequence of stopping times which are as close as possible to the unknown times of disorders at which the observation process changes its probability ...
This is a companion note to Zinde-Walsh (2010), arXiv:1009.4217v1[MATH.ST], to clarify and extend results on identification in a number of problems that lead to a system of convolution equations. Exam...
The correspondence between the cross-entropymethod and the zero-variance approximation to simulate a rare event problem in Markov chains is shown. This leads to a sufficient condition that the cross...
When testing a large number of independent hypotheses, three different questions are of interest: are some hypotheses true alternatives? How many of them? Which of them? These questions give rise to...
The Three Doors Problem, or Monty Hall Problem, is familiar to statisticians as a paradox in elementary probability theory often found in elementary probability texts (especially in their exercises ...
Upon reading the paper Efficient Likelihood Estimation in State Space Models by Cheng-Der Fuh I found a number of problems in the formulations and a number of mathematical errors. Together, these fi...
This paper considers estimation of the predictive density for a normal linear model with unknown variance under -divergence loss for −1   1. We first give a general canonical form for the...

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