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» Learning Finite-State Models for Machine Translation
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ICML
2005
IEEE
14 years 10 months ago
Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM
This paper explores the issue of recognizing, generalizing and reproducing arbitrary gestures. We aim at extracting a representation that encapsulates only the key aspects of the ...
Sylvain Calinon, Aude Billard
COLING
2010
13 years 4 months ago
Finite-state Scriptural Translation
We use robust and fast Finite-State Machines (FSMs) to solve scriptural translation problems. We describe a phonetico-morphotactic pivot UIT (universal intermediate transcription)...
M. G. Abbas Malik, Christian Boitet, Pushpak Bhatt...
JMLR
2011
187views more  JMLR 2011»
13 years 4 months ago
Exploitation of Machine Learning Techniques in Modelling Phrase Movements for Machine Translation
We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to learn the grammatical rules and context dependent changes using ...
Yizhao Ni, Craig Saunders, Sándor Szedm&aac...
FORTE
2008
13 years 11 months ago
Detecting Communication Protocol Security Flaws by Formal Fuzz Testing and Machine Learning
Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in a...
Guoqiang Shu, Yating Hsu, David Lee
ICML
2006
IEEE
14 years 10 months ago
PAC model-free reinforcement learning
For a Markov Decision Process with finite state (size S) and action spaces (size A per state), we propose a new algorithm--Delayed Q-Learning. We prove it is PAC, achieving near o...
Alexander L. Strehl, Lihong Li, Eric Wiewiora, Joh...