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» The Localization Hypothesis and Machines
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ICML
2000
IEEE
14 years 2 months ago
A Bayesian Framework for Reinforcement Learning
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
Malcolm J. A. Strens
ACL
2007
13 years 11 months ago
Improved Word-Level System Combination for Machine Translation
Recently, confusion network decoding has been applied in machine translation system combination. Due to errors in the hypothesis alignment, decoding may result in ungrammatical co...
Antti-Veikko I. Rosti, Spyridon Matsoukas, Richard...
LREC
2008
135views Education» more  LREC 2008»
13 years 11 months ago
Communicating Unknown Words in Machine Translation
A new approach to handle unknown words in machine translation is presented. The basic idea is to find definitions for the unknown words on the source language side and translate t...
Matthias Eck, Stephan Vogel, Alex Waibel
NAACL
2007
13 years 11 months ago
Source-Language Features and Maximum Correlation Training for Machine Translation Evaluation
We propose three new features for MT evaluation: source-sentence constrained n-gram precision, source-sentence reordering metrics, and discriminative unigram precision, as well as...
Ding Liu, Daniel Gildea
JMLR
2010
115views more  JMLR 2010»
13 years 4 months ago
Fast and Scalable Local Kernel Machines
A computationally efficient approach to local learning with kernel methods is presented. The Fast Local Kernel Support Vector Machine (FaLK-SVM) trains a set of local SVMs on redu...
Nicola Segata, Enrico Blanzieri