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NIPS
2008
13 years 11 months ago
Posterior Consistency of the Silverman g-prior in Bayesian Model Choice
Kernel supervised learning methods can be unified by utilizing the tools from regularization theory. The duality between regularization and prior leads to interpreting regularizat...
Zhihua Zhang, Michael I. Jordan, Dit-Yan Yeung
JMLR
2010
105views more  JMLR 2010»
13 years 4 months ago
On the Convergence Properties of Contrastive Divergence
Contrastive Divergence (CD) is a popular method for estimating the parameters of Markov Random Fields (MRFs) by rapidly approximating an intractable term in the gradient of the lo...
Ilya Sutskever, Tijmen Tieleman
NIPS
2007
13 years 11 months ago
Bundle Methods for Machine Learning
We present a globally convergent method for regularized risk minimization problems. Our method applies to Support Vector estimation, regression, Gaussian Processes, and any other ...
Alex J. Smola, S. V. N. Vishwanathan, Quoc V. Le
IR
2007
13 years 9 months ago
Regularizing query-based retrieval scores
In information retrieval, the cluster hypothesis states: closely related documents tend to be relevant to the same request. We exploit this hypothesis directly by adjusting queryb...
Fernando Diaz
NIPS
2000
13 years 11 months ago
Regularized Winnow Methods
In theory, the Winnow multiplicative update has certain advantages over the Perceptron additive update when there are many irrelevant attributes. Recently, there has been much eff...
Tong Zhang