1393 search results - page 150 / 279 » Machine Learning by Function Decomposition |
123
Voted
NIPS
2004
15 years 3 months ago
2004
Successful application of reinforcement learning algorithms often involves considerable hand-crafting of the necessary non-linear features to reduce the complexity of the value fu...
130
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ICML
2008
IEEE
16 years 2 months ago
2008
IEEE
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
128
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ICML
2009
IEEE
16 years 2 months ago
2009
IEEE
Most models of utility elicitation in decision support and interactive optimization assume a predefined set of "catalog" features over which user preferences are express...
126
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ICML
2007
IEEE
16 years 2 months ago
2007
IEEE
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
ICML
2008
IEEE
16 years 2 months ago
2008
IEEE
The central issue in representing graphstructured data instances in learning algorithms is designing features which are invariant to permuting the numbering of the vertices. We pr...