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FLAIRS
2007
15 years 7 months ago
An Argumentation Based Approach to Multi-Agent Learning
This paper addresses the issue of learning from communication among agents that work in the same domain, are capable of learning from examples, and communicate using an argumentat...
Santiago Ontañón, Enric Plaza
HIS
2007
15 years 6 months ago
Active Selection of Training Examples for Meta-Learning
Meta-Learning has been used to relate the performance of algorithms and the features of the problems being tackled. The knowledge in Meta-Learning is acquired from a set of meta-e...
Ricardo Bastos Cavalcante Prudêncio, Teresa ...
NIPS
2007
15 years 6 months ago
Active Preference Learning with Discrete Choice Data
We propose an active learning algorithm that learns a continuous valuation model from discrete preferences. The algorithm automatically decides what items are best presented to an...
Eric Brochu, Nando de Freitas, Abhijeet Ghosh
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NIPS
2007
15 years 6 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
AAAI
2006
15 years 6 months ago
Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping
Transfer learning concerns applying knowledge learned in one task (the source) to improve learning another related task (the target). In this paper, we use structure mapping, a ps...
Yaxin Liu, Peter Stone