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SVMs for Classification

• BOSER, Bernhard E., Isabelle M. GUYON and Vladimir N. VAPNIK, A Training Algorithm for Optimal Margin Classifiers [about 515]
  "Experimental results on optical character recognition problems demonstrate the good generalization obtained when compared with other learning algorithms."
  Boser, Guyon and Vapnik (1992)
  
  
• BURBIDGE, R. et al., Drug design by machine learning: support vector machines for pharmaceutical data analysis [about 40]
  "Three artificial neural networks, a radial basis function network, and a C5.0 decision tree are all outperformed by the SVM. The SVM is significantly better than all of these, bar a manually capacity-controlled neural network, which takes considerably longer to train."
  Burbidge et al. (2001)
  
  
• Classification
• DRISH, Joseph, Obtaining calibrated probability estimates from support vector classifiers: project proposal [2]
• DUDA, Richard O., Peter E. HART and David G. STORK, Pattern Classification and Scene Analysis (2nd ed.): Part 1: Pattern Classification
  "Unsupervised Learning and Clustering"
  Duda, Hart and Stork (1995)
  
  
• EVGENIOU, Theodoros and Massimiliano PONTIL, A note on the generalization performance of kernel classifiers with margin.
  Theodoros and Pontil
  
  
• GRETTON, Arthur, et al., Nonstationary Signal Classification Using Support Vector Machines
  "We show that the SV classifier outperforms alternative classification methods on this processed data."
  Gretton et al. (2001)
  
  
• LIN, Yi, 1999. Support Vector Machines and the Bayes Rule in Classification
  "it is shown that SVMs implement the Bayes rule approximately by targeting at some interesting classification functions."
• MANEVITZ, Larry M. and Malik YOUSEF, 2001. One-Class SVMs for Document Classification
• PONTIL, Massimiliano, Ryan RIFKIN and Theodoros EVGENIOU, From Regression to Classification in Support Vector Machines
• SALOMON, Jesper, Support Vector Machines for Phoneme Classification
• SMITH, Nathan and Mahesan NIRANJAN, Data-Dependent Kernels in SVM Classification of Speech Patterns
• VERRI, Alessandro, 9.520: Class 14: Support Vector Machines for Classification
• VANNEREM, P., et al., 1999. Classifying LEP Data with Support Vector Algorithms
• ZHANG, Rong and Alex RUDNICKY, Word Level Confidence Annotation using Combinations of Features