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» Support vector machine learning for image retrieval
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ICML
2003
IEEE
14 years 9 months ago
The Pre-Image Problem in Kernel Methods
In this paper, we address the problem of finding the pre-image of a feature vector in the feature space induced by a kernel. This is of central importance in some kernel applicatio...
James T. Kwok, Ivor W. Tsang
JMLR
2008
133views more  JMLR 2008»
13 years 8 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
ICML
2008
IEEE
14 years 9 months ago
Semi-supervised learning of compact document representations with deep networks
Finding good representations of text documents is crucial in information retrieval and classification systems. Today the most popular document representation is based on a vector ...
Marc'Aurelio Ranzato, Martin Szummer
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
14 years 8 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
TRECVID
2008
13 years 9 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...