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Support Vector Machine

254 directly classified papers

Papers per year

Papers

Fast Prediction for Large-Scale Kernel Machines NIPS 2014
The Coherent Loss Function for Classification ICML 2014
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization ICML 2014
Linear Time Solver for Primal SVM ICML 2014
Scaling SVM and Least Absolute Deviations via Exact Data Reduction ICML 2014
On Robustness and Regularization of Structural Support Vector Machines ICML 2014
DivMCuts: Faster Training of Structural SVMs with Diverse M-Best Cutting-Planes AISTATS 2013
BudgetedSVM: A Toolbox for Scalable SVM Approximations JMLR 2013
Learning and Calibrating Per-Location Classifiers for Visual Place Recognition CVPR 2013
Block-Coordinate Frank-Wolfe Optimization for Structural SVMs ICML 2013
Convex formulations of radius-margin based Support Vector Machines ICML 2013
Learning Optimally Sparse Support Vector Machines ICML 2013
Local Deep Kernel Learning for Efficient Non-linear SVM Prediction ICML 2013
Online Kernel Learning with a Near Optimal Sparsity Bound ICML 2013
Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines ICML 2013
Safe Screening of Non-Support Vectors in Pathwise SVM Computation ICML 2013
Contextual Hypergraph Modeling for Salient Object Detection ICCV 2013
Group Norm for Learning Structured SVMs with Unstructured Latent Variables ICCV 2013
Space-Time Robust Representation for Action Recognition ICCV 2013
From Point to Set: Extend the Learning of Distance Metrics ICCV 2013
Poselet Key-Framing: A Model for Human Activity Recognition CVPR 2013
From N to N+1: Multiclass Transfer Incremental Learning CVPR 2013
Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach AISTATS 2012
A Simple Geometric Interpretation of SVM using Stochastic Adversaries AISTATS 2012
Breaking the Curse of Kernelization: Budgeted Stochastic Gradient Descent for Large-Scale SVM Training JMLR 2012