support vector machine

Classification with a Reject Option using a Hinge Loss JMLR 2008 Discriminative Learning of Max-Sum Classifiers JMLR 2008 Estimating the Confidence Interval for Prediction Errors of Support Vector Machine Classifiers JMLR 2008 Extended Grassmann Kernels for Subspace-Based Learning NeurIPS 2008 Fast Rates for Regularized Objectives NeurIPS 2008 LIBLINEAR: A Library for Large Linear Classification JMLR 2008 Max-margin Classification of Data with Absent Features JMLR 2008 Nearly Uniform Validation Improves Compression-Based Error Bounds JMLR 2008 On the Generalization Ability of Online Strongly Convex Programming Algorithms NeurIPS 2008 On the Suitable Domain for SVM Training in Image Coding JMLR 2008 Optimization Techniques for Semi-Supervised Support Vector Machines JMLR 2008 Performance analysis for L\_2 kernel classification NeurIPS 2008 Relative Margin Machines NeurIPS 2008 Scalable Algorithms for String Kernels with Inexact Matching NeurIPS 2008 SimpleMKL JMLR 2008 Sparsity of SVMs that use the epsilon-insensitive loss NeurIPS 2008 Support Vector Machinery for Infinite Ensemble Learning JMLR 2008 Support Vector Machines with a Reject Option NeurIPS 2008 Tighter Bounds for Structured Estimation NeurIPS 2008 Trust Region Newton Method for Logistic Regression JMLR 2008 An Analysis of Inference with the Universum NeurIPS 2007 A Randomized Algorithm for Large Scale Support Vector Learning NeurIPS 2007 A Risk Minimization Principle for a Class of Parzen Estimators NeurIPS 2007 Bundle Methods for Machine Learning NeurIPS 2007 Comments on the “Core Vector Machines: Fast SVM Training on Very Large Data Sets" JMLR 2007