kernel methods

Variance Reduced Online Gradient Descent for Kernelized Pairwise Learning with Limited Memory ACML 2023 What Can Be Learnt With Wide Convolutional Neural Networks? ICML 2023 Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models NeurIPS 2023 Accurate and Scalable Gaussian Processes for Fine-Grained Air Quality Inference AAAI 2022 A Consolidated Cross-Validation Algorithm for Support Vector Machines via Data Reduction NeurIPS 2022 Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization AISTATS 2022 Additive Gaussian Processes Revisited ICML 2022 A Distance Covariance-based Kernel for Nonlinear Causal Clustering in Heterogeneous Populations CLeaR 2022 Adversarial Concept Erasure in Kernel Space EMNLP 2022 A Kernelised Stein Statistic for Assessing Implicit Generative Models NeurIPS 2022 A Kernel Two-Sample Test for Functional Data JMLR 2022 A Model-Agnostic Randomized Learning Framework based on Random Hypothesis Subspace Sampling ICML 2022 An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings ICML 2022 A permutation-free kernel two-sample test NeurIPS 2022 A Perturbation-Based Kernel Approximation Framework JMLR 2022 Approximate Bayesian Computation via Classification JMLR 2022 Approximation and Learning with Deep Convolutional Models: a Kernel Perspective ICLR 2022 A Random Matrix Perspective on Mixtures of Nonlinearities in High Dimensions AISTATS 2022 A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits NeurIPS 2022 A Witness Two-Sample Test AISTATS 2022 Bayesian Optimization over Permutation Spaces AAAI 2022 Bezier Gaussian Processes for Tall and Wide Data NeurIPS 2022 Causal inference with treatment measurement error: a nonparametric instrumental variable approach UAI 2022 Communication Efficient Distributed Learning for Kernelized Contextual Bandits NeurIPS 2022 Concept Activation Regions: A Generalized Framework For Concept-Based Explanations NeurIPS 2022