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» On Unbiased Linear Approximations
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JMLR
2010
129views more  JMLR 2010»
14 years 5 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert
SIAMNUM
2010
150views more  SIAMNUM 2010»
14 years 5 months ago
Quasi-Optimal Convergence Rate of an Adaptive Discontinuous Galerkin Method
We analyze an adaptive discontinuous finite element method (ADFEM) for symmetric second order linear elliptic operators. The method is formulated on nonconforming meshes made of si...
Andrea Bonito, Ricardo H. Nochetto
108
Voted
TMC
2012
13 years 18 days ago
A Statistical Mechanics-Based Framework to Analyze Ad Hoc Networks with Random Access
—Characterizing the performance of ad hoc networks is one of the most intricate open challenges; conventional ideas based on information-theoretic techniques and inequalities hav...
Sunil Srinivasa, Martin Haenggi
ICML
2002
IEEE
15 years 11 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans
76
Voted
ICCV
2005
IEEE
16 years 3 days ago
A Graph Cut Algorithm for Generalized Image Deconvolution
The goal of deconvolution is to recover an image x from its convolution with a known blurring function. This is equivalent to inverting the linear system y = Hx. In this paper we ...
Ashish Raj, Ramin Zabih