Kernel Methods

The Fast Kernel Transform AISTATS 2022 The Teaching Dimension of Regularized Kernel Learners ICML 2022 TransBoost: A Boosting-Tree Kernel Transfer Learning Algorithm for Improving Financial Inclusion AAAI 2022 Value Function Approximations via Kernel Embeddings for No-Regret Reinforcement Learning ACML 2022 Weisfeiler and Leman Go Walking: Random Walk Kernels Revisited NeurIPS 2022 What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? NeurIPS 2022 Active Slices for Sliced Stein Discrepancy ICML 2021 An Aligned Subgraph Kernel Based on Discrete-Time Quantum Walk ACML 2021 Analyzing the discrepancy principle for kernelized spectral filter learning algorithms JMLR 2021 Application of kernel hypothesis testing on set-valued data UAI 2021 A Temporal Kernel Approach for Deep Learning with Continuous-time Information ICLR 2021 Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression ICML 2021 Deep Equals Shallow for ReLU Networks in Kernel Regimes ICLR 2021 Deep kernel processes ICML 2021 Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS ICLR 2021 Distributed Nyström Kernel Learning with Communications ICML 2021 Domain Generalization by Marginal Transfer Learning JMLR 2021 Double Machine Learning Density Estimation for Local Treatment Effects with Instruments NeurIPS 2021 Effective Meta-Regularization by Kernelized Proximal Regularization NeurIPS 2021 Entangled Kernels - Beyond Separability JMLR 2021 Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients AAAI 2021 Fast Sketching of Polynomial Kernels of Polynomial Degree ICML 2021 Generalization Properties of hyper-RKHS and its Applications JMLR 2021 GSPL: A Succinct Kernel Model for Group-Sparse Projections Learning of Multiview Data IJCAI 2021 Hierarchical Multiple Kernel Clustering AAAI 2021