kernel methods

Learning Networks of Heterogeneous Influence NeurIPS 2012 Max-Margin Ratio Machine ACML 2012 Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming JMLR 2012 Multi Kernel Learning with Online-Batch Optimization JMLR 2012 Non-parametric Approximate Dynamic Programming via the Kernel Method NeurIPS 2012 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NeurIPS 2012 On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization NeurIPS 2012 On the Convergence Rate of -Norm Multiple Kernel Learning JMLR 2012 Optimal kernel choice for large-scale two-sample tests NeurIPS 2012 Pairwise Support Vector Machines and their Application to Large Scale Problems JMLR 2012 Persistent Homology for Learning Densities with Bounded Support NeurIPS 2012 Q-MKL: Matrix-induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging NeurIPS 2012 Sampling Methods for the Nyström Method JMLR 2012 Semantic Kernel Forests from Multiple Taxonomies NeurIPS 2012 Supervised Learning with Similarity Functions NeurIPS 2012 The Lovász ϑ function, SVMs and finding large dense subgraphs NeurIPS 2012 The representer theorem for Hilbert spaces: a necessary and sufficient condition NeurIPS 2012 Toward Understanding Complex Spaces: Graph Laplacians on Manifolds with Singularities and Boundaries COLT 2012 Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity NeurIPS 2012 A Non-Parametric Approach to Dynamic Programming NeurIPS 2011 Bayesian Generalized Kernel Mixed Models JMLR 2011 Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information ACML 2011 Cross-Domain Object Matching with Model Selection AISTATS 2011 Double Updating Online Learning JMLR 2011 Generalizing from Several Related Classification Tasks to a New Unlabeled Sample NeurIPS 2011