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ICML
2009
IEEE
16 years 3 months ago
PAC-Bayesian learning of linear classifiers
We present a general PAC-Bayes theorem from which all known PAC-Bayes risk bounds are obtained as particular cases. We also propose different learning algorithms for finding linea...
Alexandre Lacasse, François Laviolette, Mar...
146
Voted
IJCNN
2008
IEEE
15 years 9 months ago
Sparse support vector machines trained in the reduced empirical feature space
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Kazuki Iwamura, Shigeo Abe
121
Voted
IPCO
2008
114views Optimization» more  IPCO 2008»
15 years 4 months ago
The Stochastic Machine Replenishment Problem
We study the stochastic machine replenishment problem, which is a canonical special case of closed multiclass queuing systems in Markov decision theory. The problem models the sche...
Kamesh Munagala, Peng Shi
126
Voted
ANNPR
2006
Springer
15 years 6 months ago
Incremental Training of Support Vector Machines Using Truncated Hypercones
We discuss incremental training of support vector machines in which we approximate the regions, where support vector candidates exist, by truncated hypercones. We generate the trun...
Shinya Katagiri, Shigeo Abe
97
Voted
NIPS
2007
15 years 4 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