kernel methods

On Relevant Dimensions in Kernel Feature Spaces JMLR 2008 Regularized Policy Iteration NeurIPS 2008 Relative Margin Machines NeurIPS 2008 Robust Kernel Principal Component Analysis NeurIPS 2008 Scalable Algorithms for String Kernels with Inexact Matching NeurIPS 2008 Shark JMLR 2008 SimpleMKL JMLR 2008 Sparsity of SVMs that use the epsilon-insensitive loss NeurIPS 2008 Supervised Bipartite Graph Inference NeurIPS 2008 Supervised Dictionary Learning NeurIPS 2008 Supervised Exponential Family Principal Component Analysis via Convex Optimization NeurIPS 2008 Support Vector Machinery for Infinite Ensemble Learning JMLR 2008 Support Vector Machines with a Reject Option NeurIPS 2008 Universal Multi-Task Kernels JMLR 2008 A Kernel Statistical Test of Independence NeurIPS 2007 An Analysis of Inference with the Universum NeurIPS 2007 A Risk Minimization Principle for a Class of Parzen Estimators NeurIPS 2007 Characterizing the Function Space for Bayesian Kernel Models JMLR 2007 Classification via Minimum Incremental Coding Length (MICL) NeurIPS 2007 Colored Maximum Variance Unfolding NeurIPS 2007 Convex Learning with Invariances NeurIPS 2007 DIFFRAC: a discriminative and flexible framework for clustering NeurIPS 2007 Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation NeurIPS 2007 Discriminative K-means for Clustering NeurIPS 2007 Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization NeurIPS 2007