1224 search results - page 63 / 245 » On the Optimality of the Dimensionality Reduction Method |
152
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NIPS
2001
15 years 7 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
156
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KDD
2003
ACM
16 years 6 months ago
2003
ACM
Dimensionality reduction via Random Projections has attracted considerable attention in recent years. The approach has interesting theoretical underpinnings and offers computation...
148
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IJCAI
2007
15 years 7 months ago
2007
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
173
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NIPS
1997
15 years 7 months ago
1997
Nonlinear dimensionality reduction is formulated here as the problem of trying to find a Euclidean feature-space embedding of a set of observations that preserves as closely as p...
185
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CORR
2012
Springer
14 years 1 months ago
2012
Springer
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the p-norm of the parameters. We discuss several implications ...