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» Training a Selection Function for Extraction
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ACL
2009
13 years 5 months ago
Optimizing Word Alignment Combination For Phrase Table Training
Combining word alignments trained in two translation directions has mostly relied on heuristics that are not directly motivated by intended applications. We propose a novel method...
Yonggang Deng, Bowen Zhou
JMLR
2010
129views more  JMLR 2010»
13 years 2 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
IVC
2002
90views more  IVC 2002»
13 years 7 months ago
Force field energy functionals for image feature extraction
Ears are an emergent biometric accruing application advantages including no requirement for subject contact and acquisition without demand. To recognize a subject's ear, we a...
David J. Hurley, Mark S. Nixon, John N. Carter
ICANN
2005
Springer
14 years 1 months ago
Training of Support Vector Machines with Mahalanobis Kernels
Abstract. Radial basis function (RBF) kernels are widely used for support vector machines. But for model selection, we need to optimize the kernel parameter and the margin paramete...
Shigeo Abe
ICASSP
2011
IEEE
12 years 11 months ago
Feature selection based on Multiple Kernel Learning for single-channel sound source localization using the acoustic transfer fun
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work [1], we discussed the single-channel sound source localization...
Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki