Kernel Methods

Persistence weighted Gaussian kernel for topological data analysis ICML 2016 Preconditioning Kernel Matrices ICML 2016 Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels JMLR 2016 Random Features for Sparse Signal Classification CVPR 2016 Random Fourier Features For Operator-Valued Kernels ACML 2016 Recycling Randomness with Structure for Sublinear time Kernel Expansions ICML 2016 Robust Visual Place Recognition With Graph Kernels CVPR 2016 Sliced Wasserstein Kernels for Probability Distributions CVPR 2016 Sorting out typicality with the inverse moment matrix SOS polynomial NeurIPS 2016 SPSD Matrix Approximation vis Column Selection: Theories, Algorithms, and Extensions JMLR 2016 Streaming Kernel Principal Component Analysis AISTATS 2016 Supervised Learning with Tensor Networks NeurIPS 2016 The Multiscale Laplacian Graph Kernel NeurIPS 2016 Toward Deeper Understanding of Neural Networks: The Power of Initialization and a Dual View on Expressivity NeurIPS 2016 Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction ICML 2015 A Stable Multi-Scale Kernel for Topological Machine Learning CVPR 2015 A Structural Smoothing Framework For Robust Graph Comparison NeurIPS 2015 Cross-Domain Matching for Bag-of-Words Data via Kernel Embeddings of Latent Distributions NeurIPS 2015 Efficient Output Kernel Learning for Multiple Tasks NeurIPS 2015 Fast Randomized Kernel Ridge Regression with Statistical Guarantees NeurIPS 2015 Fast Two-Sample Testing with Analytic Representations of Probability Measures NeurIPS 2015 Geodesic Exponential Kernels: When Curvature and Linearity Conflict CVPR 2015 Halting in Random Walk Kernels NeurIPS 2015 Landmarks-Based Kernelized Subspace Alignment for Unsupervised Domain Adaptation CVPR 2015 Learning with Group Invariant Features: A Kernel Perspective. NeurIPS 2015