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Kernel interpolation with continuous volume sampling

Kernel interpolation with continuous volume sampling

International Conference on Machine Learning (ICML), 2020
22 February 2020
Ayoub Belhadji
Rémi Bardenet
P. Chainais
ArXiv (abs)PDFHTML

Papers citing "Kernel interpolation with continuous volume sampling"

16 / 16 papers shown
Repulsive Monte Carlo on the sphere for the sliced Wasserstein distance
Repulsive Monte Carlo on the sphere for the sliced Wasserstein distance
Vladimir Petrovic
Rémi Bardenet
Agnès Desolneux
173
1
0
12 Sep 2025
On the design of scalable, high-precision spherical-radial Fourier
  features
On the design of scalable, high-precision spherical-radial Fourier features
Ayoub Belhadji
Qianyu Julie Zhu
Youssef Marzouk
1.1K
1
0
23 Aug 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization
  via Probabilistic Lifting
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
410
3
0
18 Apr 2024
Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding
Monte Carlo with kernel-based Gibbs measures: Guarantees for probabilistic herding
Martin Rouault
Rémi Bardenet
Mylène Maïda
371
1
0
18 Feb 2024
Weighted least-squares approximation with determinantal point processes and generalized volume sampling
Weighted least-squares approximation with determinantal point processes and generalized volume sampling
A. Nouy
Bertrand Michel
360
4
0
21 Dec 2023
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling
Antoine Chatalic
Nicolas Schreuder
Ernesto De Vito
Lorenzo Rosasco
276
6
0
22 Nov 2023
Policy Gradient with Kernel Quadrature
Policy Gradient with Kernel Quadrature
Satoshi Hayakawa
Tetsuro Morimura
OffRLBDL
385
1
0
23 Oct 2023
Signal reconstruction using determinantal sampling
Signal reconstruction using determinantal sampling
Ayoub Belhadji
Rémi Bardenet
P. Chainais
187
5
0
13 Oct 2023
An analysis of Ermakov-Zolotukhin quadrature using kernels
An analysis of Ermakov-Zolotukhin quadrature using kernelsNeural Information Processing Systems (NeurIPS), 2023
Ayoub Belhadji
183
14
0
03 Sep 2023
Kernel quadrature with randomly pivoted Cholesky
Kernel quadrature with randomly pivoted CholeskyNeural Information Processing Systems (NeurIPS), 2023
Ethan N. Epperly
Elvira Moreno
359
11
0
06 Jun 2023
Sampling-based Nyström Approximation and Kernel Quadrature
Sampling-based Nyström Approximation and Kernel QuadratureInternational Conference on Machine Learning (ICML), 2023
Satoshi Hayakawa
Harald Oberhauser
Terry Lyons
444
18
0
23 Jan 2023
On estimating the structure factor of a point process, with applications
  to hyperuniformity
On estimating the structure factor of a point process, with applications to hyperuniformityStatistics and computing (Stat. Comput.), 2022
D. Hawat
G. Gautier
Rémi Bardenet
R. Lachièze-Rey
289
14
0
16 Mar 2022
Determinantal point processes based on orthogonal polynomials for
  sampling minibatches in SGD
Determinantal point processes based on orthogonal polynomials for sampling minibatches in SGD
Rémi Bardenet
Subhro Ghosh
Meixia Lin
327
8
0
11 Dec 2021
Positively Weighted Kernel Quadrature via Subsampling
Positively Weighted Kernel Quadrature via SubsamplingNeural Information Processing Systems (NeurIPS), 2021
Satoshi Hayakawa
Harald Oberhauser
Terry Lyons
483
29
0
20 Jul 2021
Nonparametric estimation of continuous DPPs with kernel methods
Nonparametric estimation of continuous DPPs with kernel methodsNeural Information Processing Systems (NeurIPS), 2021
Michaël Fanuel
Rémi Bardenet
158
1
0
27 Jun 2021
Kernel Thinning
Kernel ThinningAnnual Conference Computational Learning Theory (COLT), 2021
Raaz Dwivedi
Lester W. Mackey
892
46
0
12 May 2021
1
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