3250 search results - page 139 / 650 » Parameterized Learning Complexity |
108
Voted
AAAI
2008
15 years 5 months ago
2008
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
92
Voted
UAI
1997
15 years 4 months ago
1997
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
134
Voted
NIPS
1994
15 years 4 months ago
1994
Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
120
Voted
ICML
2007
IEEE
16 years 3 months ago
2007
IEEE
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
83
Voted
ECAI
2004
Springer
15 years 8 months ago
2004
Springer
Abstract. Learning in complex contexts often requires pure induction to be supported by various kinds of meta-information. Providing such information is a critical, difficult and ...