Support Vector Machine

Augmented-SVM: Automatic space partitioning for combining multiple non-linear dynamics NeurIPS 2012 Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training JMLR 2012 Kernel Latent SVM for Visual Recognition NeurIPS 2012 Learning from Distributions via Support Measure Machines NeurIPS 2012 Learning with Recursive Perceptual Representations NeurIPS 2012 Maximum Margin Temporal Clustering AISTATS 2012 Perceptron Learning of SAT NeurIPS 2012 Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging NeurIPS 2012 Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach AISTATS 2012 Sparse Additive Machine AISTATS 2012 The Lovász ϑ function, SVMs and finding large dense subgraphs NeurIPS 2012 Unsupervised SVMs: On the Complexity of the Furthest Hyperplane Problem COLT 2012 Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity NeurIPS 2012 Advice Refinement in Knowledge-Based SVMs NeurIPS 2011 Agnostic Selective Classification NeurIPS 2011 Approximate Model Selection for Large Scale LSSVM ACML 2011 Beating SGD: Learning SVMs in Sublinear Time NeurIPS 2011 Efficient variable selection in support vector machines via the alternating direction method of multipliers AISTATS 2011 Infinite Latent SVM for Classification and Multi-task Learning NeurIPS 2011 Laplacian Support Vector Machines Trained in the Primal JMLR 2011 Learning Anchor Planes for Classification NeurIPS 2011 Learning person-object interactions for action recognition in still images NeurIPS 2011 Maximum Margin Multi-Label Structured Prediction NeurIPS 2011 Optimal learning rates for least squares SVMs using Gaussian kernels NeurIPS 2011 Guarantees for Approximate Incremental SVMs AISTATS 2010