Generalized Kernel Thinning

4 October 2021

Papers citing "Generalized Kernel Thinning"

24 / 24 papers shown

Title
Geometric Median Matching for Robust k-Subset Selection from Noisy Data Anish Acharya Sujay Sanghavi Alexandros G. Dimakis Inderjit S Dhillon AAML 53 0 0 01 Apr 2025
Low-Rank Thinning Annabelle Michael Carrell Albert Gong Abhishek Shetty Raaz Dwivedi Lester W. Mackey 53 0 0 17 Feb 2025
Supervised Kernel Thinning Albert Gong Kyuseong Choi Raaz Dwivedi 11 0 0 17 Oct 2024
Learning Counterfactual Distributions via Kernel Nearest Neighbors Kyuseong Choi Jacob Feitelberg Anish Agarwal Raaz Dwivedi OOD OffRL 24 0 0 17 Oct 2024
Efficient and Accurate Explanation Estimation with Distribution Compression Hubert Baniecki Giuseppe Casalicchio Bernd Bischl Przemyslaw Biecek FAtt 31 3 0 26 Jun 2024
Submodular Framework for Structured-Sparse Optimal Transport Piyushi Manupriya Pratik Jawanpuria Karthik S. Gurumoorthy SakethaNath Jagarlapudi Bamdev Mishra OT 46 0 0 07 Jun 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting Masaki Adachi Satoshi Hayakawa Martin Jørgensen Saad Hamid Harald Oberhauser Michael A. Osborne GP 17 3 0 18 Apr 2024
Resource-Aware Collaborative Monte Carlo Localization with Distribution Compression Nicky Zimmerman Alessandro Giusti Jérôme Guzzi 16 1 0 02 Apr 2024
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling Antoine Chatalic Nicolas Schreuder E. De Vito Lorenzo Rosasco 6 3 0 22 Nov 2023
Policy Gradient with Kernel Quadrature Satoshi Hayakawa Tetsuro Morimura OffRL BDL 8 0 0 23 Oct 2023
Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach Masaki Adachi Satoshi Hayakawa Martin Jørgensen Xingchen Wan Vu Nguyen Harald Oberhauser Michael A. Osborne 10 4 0 09 Jun 2023
Kernel quadrature with randomly pivoted Cholesky Ethan N. Epperly Elvira Moreno 11 8 0 06 Jun 2023
When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality Jose H. Blanchet Haoxuan Chen Yiping Lu Lexing Ying 20 3 0 25 May 2023
Stein $Π$ -Importance Sampling Congye Wang Ye Chen Heishiro Kanagawa Chris J. Oates 24 2 0 17 May 2023
Bayesian Reinforcement Learning with Limited Cognitive Load Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy OffRL 14 7 0 05 May 2023
Coordinating Distributed Example Orders for Provably Accelerated Training A. Feder Cooper Wentao Guo Khiem Pham Tiancheng Yuan Charlie F. Ruan Yucheng Lu Chris De Sa 24 5 0 02 Feb 2023
Sampling-based Nyström Approximation and Kernel Quadrature Satoshi Hayakawa Harald Oberhauser Terry Lyons 8 13 0 23 Jan 2023
Compress Then Test: Powerful Kernel Testing in Near-linear Time Carles Domingo-Enrich Raaz Dwivedi Lester W. Mackey 28 9 0 14 Jan 2023
Online Kernel CUSUM for Change-Point Detection S. Wei Yao Xie 6 11 0 28 Nov 2022
Distribution Compression in Near-linear Time Abhishek Shetty Raaz Dwivedi Lester W. Mackey 8 14 0 15 Nov 2021
Positively Weighted Kernel Quadrature via Subsampling Satoshi Hayakawa Harald Oberhauser Terry Lyons 17 23 0 20 Jul 2021
Kernel Thinning Raaz Dwivedi Lester W. Mackey 13 29 0 12 May 2021
Measuring Sample Quality with Kernels Jackson Gorham Lester W. Mackey 72 204 0 06 Mar 2017
A Kernel Test of Goodness of Fit Kacper P. Chwialkowski Heiko Strathmann A. Gretton BDL 86 324 0 09 Feb 2016