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TASLP
2010
138views more  TASLP 2010»
13 years 2 months ago
Glimpsing IVA: A Framework for Overcomplete/Complete/Undercomplete Convolutive Source Separation
Abstract--Independent vector analysis (IVA) is a method for separating convolutedly mixed signals that significantly reduces the occurrence of the well-known permutation problem in...
Alireza Masnadi-Shirazi, Wenyi Zhang, Bhaskar D. R...
CIKM
2009
Springer
14 years 2 months ago
Reducing the risk of query expansion via robust constrained optimization
We introduce a new theoretical derivation, evaluation methods, and extensive empirical analysis for an automatic query expansion framework in which model estimation is cast as a r...
Kevyn Collins-Thompson
ACL
2001
13 years 9 months ago
Serial Combination of Rules and Statistics: A Case Study in Czech Tagging
A hybrid system is described which combines the strength of manual rulewriting and statistical learning, obtaining results superior to both methods if applied separately. The comb...
Jan Hajic, Pavel Krbec, Pavel Kveton, Karel Oliva,...
JCB
2008
159views more  JCB 2008»
13 years 7 months ago
BayesMD: Flexible Biological Modeling for Motif Discovery
We present BayesMD, a Bayesian Motif Discovery model with several new features. Three different types of biological a priori knowledge are built into the framework in a modular fa...
Man-Hung Eric Tang, Anders Krogh, Ole Winther
JMLR
2012
11 years 10 months ago
Krylov Subspace Descent for Deep Learning
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
Oriol Vinyals, Daniel Povey