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» Sparse Recovery Using Sparse Random Matrices
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ICML
2005
IEEE
15 years 10 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
ISSAC
2004
Springer
106views Mathematics» more  ISSAC 2004»
15 years 3 months ago
Factoring polynomials via polytopes
We introduce a new approach to multivariate polynomial factorisation which incorporates ideas from polyhedral geometry, and generalises Hensel lifting. Our main contribution is to...
Fatima Abu Salem, Shuhong Gao, Alan G. B. Lauder
NAACL
2007
14 years 11 months ago
Comparing User Simulation Models For Dialog Strategy Learning
This paper explores what kind of user simulation model is suitable for developing a training corpus for using Markov Decision Processes (MDPs) to automatically learn dialog strate...
Hua Ai, Joel R. Tetreault, Diane J. Litman
CORR
2010
Springer
188views Education» more  CORR 2010»
14 years 10 months ago
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible ...
Sahand Negahban, Pradeep Ravikumar, Martin J. Wain...
ICPR
2006
IEEE
15 years 11 months ago
Using Specularities to Recover Multiple Light Sources in the Presence of Texture
Recovering multiple point light sources from a sparse set of photographs in which objects of unknown texture can move is challenging. This is because both diffuse and specular ref...
Pascal Lagger, Pascal Fua