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» Learning for Dynamic Subsumption
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JAIR
2008
135views more  JAIR 2008»
15 years 2 months ago
On Similarities between Inference in Game Theory and Machine Learning
In this paper, we elucidate the equivalence between inference in game theory and machine learning. Our aim in so doing is to establish an equivalent vocabulary between the two dom...
Iead Rezek, David S. Leslie, Steven Reece, Stephen...
JMLR
2006
169views more  JMLR 2006»
15 years 2 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
125
Voted
EUROCAST
2007
Springer
182views Hardware» more  EUROCAST 2007»
15 years 8 months ago
A k-NN Based Perception Scheme for Reinforcement Learning
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...
José Antonio Martin H., Javier de Lope Asia...
97
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CI
2002
92views more  CI 2002»
15 years 2 months ago
Model Selection in an Information Economy: Choosing What to Learn
As online markets for the exchange of goods and services become more common, the study of markets composed at least in part of autonomous agents has taken on increasing importance...
Christopher H. Brooks, Robert S. Gazzale, Rajarshi...
108
Voted
ETS
2002
IEEE
155views Hardware» more  ETS 2002»
15 years 2 months ago
The experience of practitioners with technology-enhanced teaching and learning
This paper describes a research project, which seeks to showcase the experience base of practitioners with technology-enhanced teaching and learning. A particular focus of this in...
Som Naidu, David Cunnington, Carol Jasen