Kernel Methods

Combined discriminative and generative articulated pose and non-rigid shape estimation NeurIPS 2007 Convex Learning with Invariances NeurIPS 2007 Discriminative K-means for Clustering NeurIPS 2007 Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization NeurIPS 2007 Hierarchical Penalization NeurIPS 2007 Kernel Measures of Conditional Dependence NeurIPS 2007 Kernels on Attributed Pointsets with Applications NeurIPS 2007 Learnability of Gaussians with Flexible Variances JMLR 2007 Learning Equivariant Functions with Matrix Valued Kernels JMLR 2007 Learning with Transformation Invariant Kernels NeurIPS 2007 Parallelizing Support Vector Machines on Distributed Computers NeurIPS 2007 Random Features for Large-Scale Kernel Machines NeurIPS 2007 Receptive Fields without Spike-Triggering NeurIPS 2007 Support Vector Machine Classification with Indefinite Kernels NeurIPS 2007 Testing for Homogeneity with Kernel Fisher Discriminant Analysis NeurIPS 2007 Ultrafast Monte Carlo for Statistical Summations NeurIPS 2007 Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NeurIPS 2007 Accurate Error Bounds for the Eigenvalues of the Kernel Matrix JMLR 2006 A Direct Method for Building Sparse Kernel Learning Algorithms JMLR 2006 A Kernel Method for the Two-Sample-Problem NeurIPS 2006 A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems NeurIPS 2006 An Oracle Inequality for Clipped Regularized Risk Minimizers NeurIPS 2006 Approximate Correspondences in High Dimensions NeurIPS 2006 Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees NeurIPS 2006 Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods NeurIPS 2006