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» Optimal feature selection for support vector machines
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SIGIR
2006
ACM
14 years 1 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi
SIGIR
2010
ACM
13 years 11 months ago
Self-taught hashing for fast similarity search
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is sem...
Dell Zhang, Jun Wang, Deng Cai, Jinsong Lu
KDD
2008
ACM
178views Data Mining» more  KDD 2008»
14 years 8 months ago
Training structural svms with kernels using sampled cuts
Discriminative training for structured outputs has found increasing applications in areas such as natural language processing, bioinformatics, information retrieval, and computer ...
Chun-Nam John Yu, Thorsten Joachims
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
14 years 2 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
BIOINFORMATICS
2007
151views more  BIOINFORMATICS 2007»
13 years 7 months ago
A new protein-protein docking scoring function based on interface residue properties
Motivation: Protein–protein complexes are known to play key roles in many cellular processes. However, they are often not accessible to experimental study because of their low s...
Julie Bernauer, Jérôme Azé, Jo...