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JMLR
2011
110views more  JMLR 2011»
15 years 1 months ago
Training SVMs Without Offset
We develop, analyze, and test a training algorithm for support vector machine classifiers without offset. Key features of this algorithm are a new, statistically motivated stoppi...
Ingo Steinwart, Don R. Hush, Clint Scovel
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
15 years 1 months ago
Adaptive bases for Q-learning
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Dotan Di Castro, Shie Mannor
ISBRA
2007
Springer
16 years 23 days ago
GFBA: A Biclustering Algorithm for Discovering Value-Coherent Biclusters
Clustering has been one of the most popular approaches used in gene expression data analysis. A clustering method is typically used to partition genes according to their similarity...
Xubo Fei, Shiyong Lu, Horia F. Pop, Lily R. Liang
SDM
2008
SIAM
161views Data Mining» more  SDM 2008»
15 years 8 months ago
Efficient Maximum Margin Clustering via Cutting Plane Algorithm
Maximum margin clustering (MMC) is a recently proposed clustering method, which extends the theory of support vector machine to the unsupervised scenario and aims at finding the m...
Bin Zhao, Fei Wang, Changshui Zhang
COMPUTING
2008
174views more  COMPUTING 2008»
15 years 6 months ago
Multilevel algorithms for Rannacher-Turek finite element approximation of 3D elliptic problems
Generalizing the approach of a previous work [15] the authors present multilevel preconditioners for three-dimensional (3D) elliptic problems discretized by a family of Rannacher ...
Ivan Georgiev, Johannes Kraus, Svetozar Margenov