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TNN
2010
205views Management» more  TNN 2010»
14 years 4 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
CORR
2008
Springer
113views Education» more  CORR 2008»
14 years 9 months ago
Robustness, Risk, and Regularization in Support Vector Machines
We consider two new formulations for classification problems in the spirit of support vector machines based on robust optimization. Our formulations are designed to build in prote...
Huan Xu, Shie Mannor, Constantine Caramanis
RECOMB
2002
Springer
15 years 10 months ago
Combining pairwise sequence similarity and support vector machines for remote protein homology detection
One key element in understanding the molecular machinery of the cell is to understand the meaning, or function, of each protein encoded in the genome. A very successful means of i...
Li Liao, William Stafford Noble
ICPR
2002
IEEE
15 years 10 months ago
Object Detection in Images: Run-Time Complexity and Parameter Selection of Support Vector Machines
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
Nicola Ancona, Grazia Cicirelli, Ettore Stella, Ar...
83
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NIPS
2004
14 years 11 months ago
The Entire Regularization Path for the Support Vector Machine
The support vector machine (SVM) is a widely used tool for classification. Many efficient implementations exist for fitting a two-class SVM model. The user has to supply values fo...
Trevor Hastie, Saharon Rosset, Robert Tibshirani, ...