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SIGIR
2006
ACM
14 years 3 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
GECCO
2005
Springer
186views Optimization» more  GECCO 2005»
14 years 3 months ago
Subproblem optimization by gene correlation with singular value decomposition
Several ways of using singular value decomposition (SVD), a linear algebra technique typically used for information retrieval, to decompose problems into subproblems are investiga...
Jacob G. Martin
CIKM
2004
Springer
14 years 3 months ago
Event threading within news topics
With the overwhelming volume of online news available today, there is an increasing need for automatic techniques to analyze and present news to the user in a meaningful and effi...
Ramesh Nallapati, Ao Feng, Fuchun Peng, James Alla...
SIGIR
2010
ACM
14 years 1 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
DAS
2010
Springer
13 years 8 months ago
Automatic unsupervised parameter selection for character segmentation
A major difficulty for designing a document image segmentation methodology is the proper value selection for all involved parameters. This is usually done after experimentations o...
Georgios Vamvakas, Nikolaos Stamatopoulos, Basilio...