60 search results - page 1 / 12 » A Parallel Mixture of SVMs for Very Large Scale Problems |
NIPS
2001
13 years 6 months ago
2001
Support Vector Machines (SVMs) are currently the state-of-the-art models for many classication problems but they suer from the complexity of their training algorithm which is at l...
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
SIGIR
2006
ACM
13 years 11 months ago
2006
ACM
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...
NIPS
2004
13 years 6 months ago
2004
We describe an algorithm for support vector machines (SVM) that can be parallelized efficiently and scales to very large problems with hundreds of thousands of training vectors. I...
GFKL
2007
Springer
13 years 8 months ago
2007
Springer
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...