4498 search results - page 443 / 900 » How to Invent Functions |
174
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ICML
2007
IEEE
16 years 7 months ago
2007
IEEE
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
157
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ICML
2008
IEEE
16 years 7 months ago
2008
IEEE
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in tha...
178
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ICML
2008
IEEE
16 years 7 months ago
2008
IEEE
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
148
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn ho...
163
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ICML
2005
IEEE
16 years 7 months ago
2005
IEEE
Sensorimotor data from many interesting physical interactions comprises discontinuities. While existing locally weighted learning approaches aim at learning smooth functions, we p...