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125
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ICML
2004
IEEE
16 years 1 months ago
2004
IEEE
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
128
Voted
ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Hashing based Approximate Nearest Neighbor (ANN) search has attracted much attention due to its fast query time and drastically reduced storage. However, most of the hashing metho...
128
Voted
IAT
2003
IEEE
15 years 6 months ago
2003
IEEE
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...
90
Voted
ICML
2008
IEEE
16 years 1 months ago
2008
IEEE
We consider the task of reinforcement learning in an environment in which rare significant events occur independently of the actions selected by the controlling agent. If these ev...
100
Voted
NIPS
1994
15 years 2 months ago
1994
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...