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» Feature selection for linear support vector machines
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ICPR
2000
IEEE
14 years 9 months ago
Motion Segmentation Using Feature Selection and Subspace Method Based on Shape Space
Motion segmentation using feature correspondences can be regarded as a combinatorial problem. A motion segmentation algorithm using feature selection and subspace method is propos...
Naoyuki Ichimura
ECML
2006
Springer
13 years 11 months ago
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
Alessandro Moschitti
KDD
2008
ACM
167views Data Mining» more  KDD 2008»
14 years 8 months ago
A sequential dual method for large scale multi-class linear svms
Efficient training of direct multi-class formulations of linear Support Vector Machines is very useful in applications such as text classification with a huge number examples as w...
S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang...
ECML
2004
Springer
14 years 1 months ago
Experiments in Value Function Approximation with Sparse Support Vector Regression
Abstract. We present first experiments using Support Vector Regression as function approximator for an on-line, sarsa-like reinforcement learner. To overcome the batch nature of S...
Tobias Jung, Thomas Uthmann
AIIA
2009
Springer
13 years 12 months ago
Local Kernel for Brains Classification in Schizophrenia
Abstract. In this paper a novel framework for brain classification is proposed in the context of mental health research. A learning by example method is introduced by combining loc...
Umberto Castellani, E. Rossato, Vittorio Murino, M...