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119
Voted
KDD
2008
ACM
167views Data Mining» more  KDD 2008»
16 years 4 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...
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
16 years 4 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
141
Voted
KDD
2002
ACM
186views Data Mining» more  KDD 2002»
16 years 4 months ago
Topic-conditioned novelty detection
Automated detection of the first document reporting each new event in temporally-sequenced streams of documents is an open challenge. In this paper we propose a new approach which...
Yiming Yang, Jian Zhang, Jaime G. Carbonell, Chun ...
131
Voted
KDD
2004
ACM
124views Data Mining» more  KDD 2004»
15 years 9 months ago
Incorporating prior knowledge with weighted margin support vector machines
Like many purely data-driven machine learning methods, Support Vector Machine (SVM) classifiers are learned exclusively from the evidence presented in the training dataset; thus ...
Xiaoyun Wu, Rohini K. Srihari
155
Voted
JACM
2010
208views more  JACM 2010»
15 years 2 months ago
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies
clustering of documents according to sharing of topics at multiple levels of abstraction. Given a corpus of documents, a posterior inference algorithm finds an approximation to a ...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...