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TRECVID
2008
13 years 11 months ago
ISM TRECVID2008 High-level Feature Extraction
We studied a method using support vector machines (SVMs) with walk-based graph kernels for the high-level feature extraction (HLF) task. In this method, each image is first segmen...
Tomoko Matsui, Jean-Philippe Vert, Shin'ichi Satoh...
NIPS
2004
13 years 11 months ago
Kernel Projection Machine: a New Tool for Pattern Recognition
This paper investigates the effect of Kernel Principal Component Analysis (KPCA) within the classification framework, essentially the regularization properties of this dimensional...
Laurent Zwald, Régis Vert, Gilles Blanchard...
JMLR
2006
143views more  JMLR 2006»
13 years 10 months ago
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function i...
Régis Vert, Jean-Philippe Vert
JMLR
2006
116views more  JMLR 2006»
13 years 10 months ago
Step Size Adaptation in Reproducing Kernel Hilbert Space
This paper presents an online support vector machine (SVM) that uses the stochastic meta-descent (SMD) algorithm to adapt its step size automatically. We formulate the online lear...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex ...
ML
2002
ACM
107views Machine Learning» more  ML 2002»
13 years 9 months ago
Training Invariant Support Vector Machines
Practical experience has shown that in order to obtain the best possible performance, prior knowledge about invariances of a classification problem at hand ought to be incorporated...
Dennis DeCoste, Bernhard Schölkopf