Support Vector Machine

Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006 Generalized Maximum Margin Clustering and Unsupervised Kernel Learning NeurIPS 2006 Incremental Support Vector Learning: Analysis, Implementation and Applications JMLR 2006 Large Scale Hidden Semi-Markov SVMs NeurIPS 2006 Large-Scale Sparsified Manifold Regularization NeurIPS 2006 Large Scale Transductive SVMs JMLR 2006 Max-margin classification of incomplete data NeurIPS 2006 One-Class Novelty Detection for Seizure Analysis from Intracranial EEG JMLR 2006 Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems JMLR 2006 QP Algorithms with Guaranteed Accuracy and Run Time for Support Vector Machines JMLR 2006 Step Size Adaptation in Reproducing Kernel Hilbert Space JMLR 2006 Support Vector Machines on a Budget NeurIPS 2006 Tighter PAC-Bayes Bounds NeurIPS 2006 Active Learning to Recognize Multiple Types of Plankton JMLR 2005 A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs JMLR 2005 Core Vector Machines: Fast SVM Training on Very Large Data Sets JMLR 2005 Fast Kernel Classifiers with Online and Active Learning JMLR 2005 Generalization Bounds and Complexities Based on Sparsity and Clustering for Convex Combinations of Functions from Random Classes JMLR 2005 Learning the Kernel with Hyperkernels JMLR 2005 Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application JMLR 2005 Maximum Margin Algorithms with Boolean Kernels JMLR 2005 Smooth ε-Insensitive Regression by Loss Symmetrization JMLR 2005 A Compression Approach to Support Vector Model Selection JMLR 2004 In Defense of One-Vs-All Classification JMLR 2004 Probability Estimates for Multi-class Classification by Pairwise Coupling JMLR 2004