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» Learning and Domain Adaptation
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EMNLP
2010
15 years 2 months ago
Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation
We describe a new approach to SMT adaptation that weights out-of-domain phrase pairs according to their relevance to the target domain, determined by both how similar to it they a...
George F. Foster, Cyril Goutte, Roland Kuhn
126
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IADIS
2004
15 years 6 months ago
Designing a personalized E-learning experience using learning objects
This paper aims to provide an experimental vision of the process of course creation using learning objects obtained in the <e-aula> project, a pilot e-learning system concei...
Pilar Sancho, Borja Manero, Baltasar Fernán...
GECCO
2011
Springer
276views Optimization» more  GECCO 2011»
14 years 8 months ago
Evolution of reward functions for reinforcement learning
The reward functions that drive reinforcement learning systems are generally derived directly from the descriptions of the problems that the systems are being used to solve. In so...
Scott Niekum, Lee Spector, Andrew G. Barto
NAACL
2003
15 years 5 months ago
Supervised and unsupervised PCFG adaptation to novel domains
This paper investigates adapting a lexicalized probabilistic context-free grammar (PCFG) to a novel domain, using maximum a posteriori (MAP) estimation. The MAP framework is gener...
Brian Roark, Michiel Bacchiani
NIPS
2008
15 years 6 months ago
Domain Adaptation with Multiple Sources
This paper presents a theoretical analysis of the problem of domain adaptation with multiple sources. For each source domain, the distribution over the input points as well as a h...
Yishay Mansour, Mehryar Mohri, Afshin Rostamizadeh