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» Learning Overcomplete Representations
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NIPS
2007
15 years 2 months ago
Semi-Supervised Multitask Learning
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
Qiuhua Liu, Xuejun Liao, Lawrence Carin
133
Voted
UAI
2008
15 years 2 months ago
Model-Based Bayesian Reinforcement Learning in Large Structured Domains
Model-based Bayesian reinforcement learning has generated significant interest in the AI community as it provides an elegant solution to the optimal exploration-exploitation trade...
Stéphane Ross, Joelle Pineau
105
Voted
IADIS
2004
15 years 2 months ago
Erroneous Examples as a Source of Learning in Mathematics
We analyze why and how erroneous examples can be beneficially employed in learning mathematics. The `Why' addresses reasoning and attitudes that are rarely fostered in today&...
Erica Melis
77
Voted
AAAI
1998
15 years 2 months ago
Learning to Predict User Operations for Adaptive Scheduling
Mixed-initiativesystemspresent the challengeof finding an effective level of interaction betweenhumans and computers. Machinelearning presents a promising approachto this problemi...
Melinda T. Gervasio, Wayne Iba, Pat Langley
202
Voted
IAT
2010
IEEE
14 years 10 months ago
Concept Learning Games: The Game of Query and Response
Abstract--This article deals with the issue of concept learning and tries to have a game theoretic view over the process of cooperative concept learning among agents in a multi-age...
Nima Mirbakhsh, Arman Didandeh, Mohsen Afsharchi