Kernel Methods

Neural Kernels Without Tangents ICML 2020 Online Multitask Learning with Long-Term Memory NeurIPS 2020 Random Fourier Features via Fast Surrogate Leverage Weighted Sampling AAAI 2020 Random Projections and α-Shape to Support the Kernel Design (Student Abstract) AAAI 2020 Scalable Gaussian Process Separation for Kernels with a Non-Stationary Phase ICML 2020 Sobolev Norm Learning Rates for Regularized Least-Squares Algorithms JMLR 2020 Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning NeurIPS 2020 Statistical Optimal Transport posed as Learning Kernel Embedding NeurIPS 2020 The weight function in the subtree kernel is decisive JMLR 2020 A Kernel Multiple Change-point Algorithm via Model Selection JMLR 2019 A Kernel Random Matrix-Based Approach for Sparse PCA ICLR 2019 Approximate Kernel Selection with Strong Approximate Consistency AAAI 2019 Argumentative Evidences Classification and Argument Scheme Detection Using Tree Kernels ACL 2019 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance COLT 2019 Comparing distributions: ℓ_1 geometry improves kernel two-sample testing NeurIPS 2019 Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon COLT 2019 Copula Multi-label Learning NeurIPS 2019 Distributionally Robust Optimization and Generalization in Kernel Methods NeurIPS 2019 Efficient Online Learning for Mapping Kernels on Linguistic Structures AAAI 2019 Efficient online learning with kernels for adversarial large scale problems NeurIPS 2019 Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels NeurIPS 2019 Implicit Kernel Learning AISTATS 2019 Integrating Bayesian and Discriminative Sparse Kernel Machines for Multi-class Active Learning NeurIPS 2019 Ivanov-Regularised Least-Squares Estimators over Large RKHSs and Their Interpolation Spaces JMLR 2019 KerGM: Kernelized Graph Matching NeurIPS 2019