kernel methods

Contextual Games: Multi-Agent Learning with Side Information NeurIPS 2020 Distributed Minimum Error Entropy Algorithms JMLR 2020 Divide-and-Conquer Learning with Nyström: Optimal Rate and Algorithm AAAI 2020 Dual Instrumental Variable Regression NeurIPS 2020 Dynamical Systems as Temporal Feature Spaces JMLR 2020 Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation EMNLP 2020 Fine-grained Fact Verification with Kernel Graph Attention Network ACL 2020 Finite Versus Infinite Neural Networks: an Empirical Study NeurIPS 2020 Gain with no Pain: Efficiency of Kernel-PCA by Nyström Sampling AISTATS 2020 Gaussian Sketching yields a J-L Lemma in RKHS AISTATS 2020 Generalized Leverage Score Sampling for Neural Networks NeurIPS 2020 GP-NAS: Gaussian Process Based Neural Architecture Search CVPR 2020 Hard Shape-Constrained Kernel Machines NeurIPS 2020 Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks ICLR 2020 HoMM: Higher-Order Moment Matching for Unsupervised Domain Adaptation AAAI 2020 Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space IJCAI 2020 Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nystrom method NeurIPS 2020 Interpretable Deep Gaussian Processes with Moments AISTATS 2020 Kernel Alignment Risk Estimator: Risk Prediction from Training Data NeurIPS 2020 Kernel-based Approach for Learning Causal Graphs from Mixed Data PGM 2020 Kernel Based Progressive Distillation for Adder Neural Networks NeurIPS 2020 Kernel Conditional Density Operators AISTATS 2020 Kernel Conditional Moment Test via Maximum Moment Restriction UAI 2020 Kernel-estimated Nonparametric Overlap-Based Syncytial Clustering JMLR 2020 Kernel interpolation with continuous volume sampling ICML 2020