995 search results - page 76 / 199 » Learning Useful Horn Approximations |
122
Voted
ICML
2000
IEEE
16 years 4 months ago
2000
IEEE
This paper discusses theoretical and experimental aspects of gradient-based approaches to the direct optimization of policy performance in controlled ??? ?s. We introduce ??? ?, a...
130
Voted
IJCNN
2000
IEEE
15 years 8 months ago
2000
IEEE
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...
115
Voted
WSC
2008
15 years 6 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...
138
Voted
NIPS
1994
15 years 5 months ago
1994
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
145
Voted
ICRA
2009
IEEE
15 years 1 months ago
2009
IEEE
Contextual reasoning through graphical models such as Markov Random Fields often show superior performance against local classifiers in many domains. Unfortunately, this performanc...