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» Feature selection for linear support vector machines
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ICPR
2000
IEEE
16 years 4 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
150
Voted
ECML
2006
Springer
15 years 7 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
113
Voted
KDD
2008
ACM
167views Data Mining» more  KDD 2008»
16 years 3 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
15 years 8 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
15 years 7 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...