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» Non-symmetric Support Vector Machines
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ICML
2006
IEEE
14 years 9 months ago
Permutation invariant SVMs
We extend Support Vector Machines to input spaces that are sets by ensuring that the classifier is invariant to permutations of subelements within each input. Such permutations in...
Pannagadatta K. Shivaswamy, Tony Jebara
IJCAI
2003
13 years 9 months ago
Approximate Policy Iteration using Large-Margin Classifiers
We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
Michail G. Lagoudakis, Ronald Parr
JMLR
2010
185views more  JMLR 2010»
13 years 2 months ago
Multiple Kernel Learning on the Limit Order Book
Simple features constructed from order book data for the EURUSD currency pair were used to construct a set of kernels. These kernels were used both individually and simultaneously...
Tristan Fletcher, Zakria Hussain, John Shawe-Taylo...
COLT
2008
Springer
13 years 10 months ago
How Local Should a Learning Method Be?
We consider the question of why modern machine learning methods like support vector machines outperform earlier nonparametric techniques like kNN. Our approach investigates the lo...
Alon Zakai, Yaacov Ritov
JMLR
2011
148views more  JMLR 2011»
13 years 3 months ago
Multitask Sparsity via Maximum Entropy Discrimination
A multitask learning framework is developed for discriminative classification and regression where multiple large-margin linear classifiers are estimated for different predictio...
Tony Jebara