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AAAI
2008
15 years 9 months ago
Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker
We propose an opponent modeling approach for no-limit Texas hold-em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relat...
Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, K...
INFORMATICALT
2010
110views more  INFORMATICALT 2010»
15 years 4 months ago
From XML to Relational Models
For many businesses and organizations, the achievement of interoperability has proven to be a highly desirable goal. However, without efficient schema mapping mechanisms or models ...
Elena Castro, Dolores Cuadra, Manuel Velasco
184
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ECCV
2008
Springer
16 years 8 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
WCRE
2009
IEEE
16 years 1 months ago
Domain Feature Model Recovery from Multiple Applications Using Data Access Semantics and Formal Concept Analysis
Feature models are widely employed in domainspecific software development to specify the domain requirements with commonality and variability. A feature model is usually construct...
Yiming Yang, Xin Peng, Wenyun Zhao
COLT
2005
Springer
16 years 9 days ago
Separating Models of Learning from Correlated and Uncorrelated Data
We consider a natural framework of learning from correlated data, in which successive examples used for learning are generated according to a random walk over the space of possibl...
Ariel Elbaz, Homin K. Lee, Rocco A. Servedio, Andr...