kernel matrix

Fast Randomized Kernel Ridge Regression with Statistical Guarantees NeurIPS 2015 Fixed-point algorithms for learning determinantal point processes ICML 2015 On the Complexity of Learning with Kernels COLT 2015 Efficient Algorithms and Error Analysis for the Modified Nystrom Method AISTATS 2014 Expectation-Maximization for Learning Determinantal Point Processes NeurIPS 2014 Memory Efficient Kernel Approximation ICML 2014 Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels ICML 2013 Nyström Approximation for Large-Scale Determinantal Processes AISTATS 2013 Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification ACML 2013 Revisiting the Nystrom method for improved large-scale machine learning ICML 2013 Sharp analysis of low-rank kernel matrix approximations COLT 2013 Algorithms for Learning Kernels Based on Centered Alignment JMLR 2012 A new metric on the manifold of kernel matrices with application to matrix geometric means NeurIPS 2012 Metric and Kernel Learning Using a Linear Transformation JMLR 2012 Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison NeurIPS 2012 Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach AISTATS 2012 A novel greedy algorithm for Nyström approximation AISTATS 2011 Learning low-rank output kernels ACML 2011 Support Vector Machines Under Adversarial Label Noise ACML 2011 Graph Kernels JMLR 2010 Inductive Regularized Learning of Kernel Functions NeurIPS 2010 Analysis of SVM with Indefinite Kernels NeurIPS 2009 Ensemble Nystrom Method NeurIPS 2009 Low-Rank Kernel Learning with Bregman Matrix Divergences JMLR 2009 Semi-supervised Learning using Sparse Eigenfunction Bases NeurIPS 2009