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Optimally-Weighted Herding is Bayesian Quadrature

Conference on Uncertainty in Artificial Intelligence (UAI), 2012

9 August 2014

Papers citing "Optimally-Weighted Herding is Bayesian Quadrature"

50 / 54 papers shown

Title
Stationary MMD Points for Cubature Zonghao Chen Toni Karvonen Heishiro Kanagawa F. Briol Chris J. Oates 240 0 0 27 May 2025
Solving the Cold Start Problem on One's Own as an End User via Preference Transfer Ryoma Sato 213 0 0 18 Feb 2025
Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models Yulei Qin Yuncheng Yang Pengcheng Guo Gang Li Hang Shao Yuchen Shi Zihan Xu Yun Gu Ke Li Xing Sun ALM 659 21 0 31 Dec 2024
Deterministic Fokker-Planck Transport -- With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo Ilja Klebanov OT 112 0 0 11 Oct 2024
Generalized Coverage for More Robust Low-Budget Active Learning Wonho Bae Junhyug Noh Danica J. Sutherland 343 7 0 16 Jul 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 348 3 0 18 Apr 2024
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling Antoine Chatalic Nicolas Schreuder Ernesto De Vito Lorenzo Rosasco 212 6 0 22 Nov 2023
Policy Gradient with Kernel Quadrature Satoshi Hayakawa Tetsuro Morimura OffRL BDL 292 1 0 23 Oct 2023
An analysis of Ermakov-Zolotukhin quadrature using kernelsNeural Information Processing Systems (NeurIPS), 2023 Ayoub Belhadji 152 14 0 03 Sep 2023
Adaptive Batch Sizes for Active Learning A Probabilistic Numerics ApproachInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Masaki Adachi Satoshi Hayakawa Martin Jørgensen Xingchen Wan Vu Nguyen Harald Oberhauser Michael A. Osborne 263 6 0 09 Jun 2023
Kernel quadrature with randomly pivoted CholeskyNeural Information Processing Systems (NeurIPS), 2023 Ethan N. Epperly Elvira Moreno 301 10 0 06 Jun 2023
When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax OptimalityNeural Information Processing Systems (NeurIPS), 2023 Jose H. Blanchet Haoxuan Chen Yiping Lu Lexing Ying 159 5 0 25 May 2023
Biological Sequence Kernels with Guaranteed Flexibility Alan N. Amin Eli N. Weinstein D. Marks 185 7 0 06 Apr 2023
SOBER: Highly Parallel Bayesian Optimization and Bayesian Quadrature over Discrete and Mixed Spaces Masaki Adachi Satoshi Hayakawa Saad Hamid Martin Jørgensen Harald Oberhauser Michael A. Osborne 362 7 0 27 Jan 2023
Sampling-based Nyström Approximation and Kernel QuadratureInternational Conference on Machine Learning (ICML), 2023 Satoshi Hayakawa Harald Oberhauser Terry Lyons 344 16 0 23 Jan 2023
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel RecombinationNeural Information Processing Systems (NeurIPS), 2022 Masaki Adachi Satoshi Hayakawa Martin Jørgensen Harald Oberhauser Michael A. Osborne 252 25 0 09 Jun 2022
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert SpacesNeural Information Processing Systems (NeurIPS), 2022 Mojmír Mutný Andreas Krause 253 12 0 26 May 2022
Estimating Rényi's $α$ -Cross-Entropies in a Matrix-Based Way I. Sledge José C. Príncipe 167 0 0 24 Sep 2021
Positively Weighted Kernel Quadrature via SubsamplingNeural Information Processing Systems (NeurIPS), 2021 Satoshi Hayakawa Harald Oberhauser Terry Lyons 386 28 0 20 Jul 2021
Compressed particle methods for expensive models with application in Astronomy and Remote SensingIEEE Transactions on Aerospace and Electronic Systems (T-AES), 2021 Luca Martino Victor Elvira J. Lopez-Santiago Gustau Camps-Valls 144 4 0 18 Jul 2021
Compressed Monte Carlo with application in particle filteringInformation Sciences (Inf. Sci.), 2021 Luca Martino Victor Elvira 137 38 0 18 Jul 2021
Sparse solutions of the kernel herding algorithm by improved gradient approximation Kazuma Tsuji Ken’ichiro Tanaka 168 0 0 17 May 2021
Sampling Permutations for Shapley Value EstimationJournal of machine learning research (JMLR), 2021 Rory Mitchell Joshua N. Cooper E. Frank G. Holmes 237 158 0 25 Apr 2021
Performance analysis of greedy algorithms for minimising a Maximum Mean DiscrepancyStatistics and computing (Stat Comput), 2021 L. Pronzato 160 16 0 19 Jan 2021
Optimal quantisation of probability measures using maximum mean discrepancy Onur Teymur Jackson Gorham M. Riabiz Chris J. Oates 272 30 0 14 Oct 2020
Kernel interpolation with continuous volume samplingInternational Conference on Machine Learning (ICML), 2020 Ayoub Belhadji Rémi Bardenet P. Chainais 112 25 0 22 Feb 2020
Learning Sparse Distributions using Iterative Hard ThresholdingNeural Information Processing Systems (NeurIPS), 2019 Jacky Y. Zhang Rajiv Khanna Anastasios Kyrillidis Oluwasanmi Koyejo 132 5 0 29 Oct 2019
Geometric Rates of Convergence for Kernel-based Sampling AlgorithmsConference on Uncertainty in Artificial Intelligence (UAI), 2019 Rajiv Khanna Liam Hodgkinson Michael W. Mahoney 181 2 0 19 Jul 2019
Kernel quadrature with DPPsNeural Information Processing Systems (NeurIPS), 2019 Ayoub Belhadji Rémi Bardenet P. Chainais 192 41 0 18 Jun 2019
Sparse Variational Inference: Bayesian Coresets from ScratchNeural Information Processing Systems (NeurIPS), 2019 Trevor Campbell Boyan Beronov 187 39 0 07 Jun 2019
Convergence Guarantees for Adaptive Bayesian Quadrature MethodsNeural Information Processing Systems (NeurIPS), 2019 Motonobu Kanagawa Philipp Hennig 183 39 0 24 May 2019
Fast Approximation and Estimation Bounds of Kernel Quadrature for Infinitely Wide Models Sho Sonoda 171 0 0 02 Feb 2019
On the positivity and magnitudes of Bayesian quadrature weights Toni Karvonen Motonobu Kanagawa Simo Särkkä 190 15 0 20 Dec 2018
Interpreting Black Box Predictions using Fisher Kernels Rajiv Khanna Been Kim Joydeep Ghosh Oluwasanmi Koyejo FAtt 243 112 0 23 Oct 2018
Bayesian quadrature and energy minimization for space-filling design L. Pronzato A. Zhigljavsky 216 9 0 31 Aug 2018
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences Motonobu Kanagawa Philipp Hennig Dino Sejdinovic Bharath K. Sriperumbudur GP BDL 236 381 0 06 Jul 2018
Bayesian posterior approximation via greedy particle optimization Futoshi Futami Zhenghang Cui Issei Sato Masashi Sugiyama 260 23 0 21 May 2018
Bayesian Quadrature for Multiple Related Integrals Xiaoyue Xi François‐Xavier Briol Mark Girolami 376 41 0 12 Jan 2018
On Data-Dependent Random Features for Improved Generalization in Supervised LearningAAAI Conference on Artificial Intelligence (AAAI), 2017 Shahin Shahrampour Ahmad Beirami Vahid Tarokh 109 27 0 19 Dec 2017
Convergence Analysis of Deterministic Kernel-Based Quadrature Rules in Misspecified Settings Motonobu Kanagawa Bharath K. Sriperumbudur Kenji Fukumizu 287 48 0 01 Sep 2017
On the Sampling Problem for Kernel QuadratureInternational Conference on Machine Learning (ICML), 2017 François‐Xavier Briol Chris J. Oates Jon Cockayne W. Chen Mark Girolami 201 29 0 11 Jun 2017
Data-driven Random Fourier Features using Stein Effect Wei-Cheng Chang Chun-Liang Li Yiming Yang Barnabás Póczós 128 30 0 23 May 2017
Fully symmetric kernel quadrature Toni Karvonen Simo Särkkä 184 29 0 18 Mar 2017
Herding Generalizes Diverse M -Best Solutions Ece Ozkan Gemma Roig O. Goksel Xavier Boix 141 0 0 14 Nov 2016
Black-box Importance Sampling Qiang Liu Jason D. Lee FAtt 150 76 0 17 Oct 2016
Uncertain programming model for multi-item solid transportation problemInternational Journal of Machine Learning and Cybernetics (IJMLC), 2016 Hasan Dalman 357 803 0 31 May 2016
Monte Carlo with Determinantal Point Processes Rémi Bardenet A. Hardy 223 85 0 02 May 2016
Probabilistic Integration: A Role in Statistical Computation? François‐Xavier Briol Chris J. Oates Mark Girolami Michael A. Osborne Dino Sejdinovic 311 56 0 03 Dec 2015
Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical GuaranteesNeural Information Processing Systems (NeurIPS), 2015 François‐Xavier Briol Chris J. Oates Mark Girolami Michael A. Osborne 299 96 0 08 Jun 2015
On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions Francis R. Bach 245 34 0 24 Feb 2015