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ICML
2003
IEEE
16 years 7 months ago
SimpleSVM
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set usin...
S. V. N. Vishwanathan, Alex J. Smola, M. Narasimha...
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 7 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
174
Voted
KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 7 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
AVSS
2009
IEEE
16 years 1 months ago
Towards Generic Detection of Unusual Events in Video Surveillance
—In this paper, we consider the challenging problem of unusual event detection in video surveillance systems. The proposed approach makes a step toward generic and automatic dete...
Ivan Ivanov, Frédéric Dufaux, Thien ...
CIDM
2009
IEEE
16 years 1 months ago
An empirical study of bagging and boosting ensembles for identifying faulty classes in object-oriented software
—  Identifying faulty classes in object-oriented software is one of the important software quality assurance activities. This paper empirically investigates the application of t...
Hamoud I. Aljamaan, Mahmoud O. Elish