Improved learning theory for kernel distribution regression with two-stage sampling

28 January 2025

François Bachoc

Louis Bethune

Alberto González Sanz

Jean-Michel Loubes

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Papers citing "Improved learning theory for kernel distribution regression with two-stage sampling"

24 / 24 papers shown

Title
Wasserstein Spatial Depth François Bachoc Alberto González Sanz Jean-Michel Loubes Yisha Yao 66 1 0 16 Nov 2024
Weak Limits for Empirical Entropic Optimal Transport: Beyond Smooth Costs Alberto González Sanz Shayan Hundrieser OT 39 10 0 16 May 2023
Gaussian Processes on Distributions based on Regularized Optimal Transport François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes GP OT 53 8 0 12 Oct 2022
Weak limits of entropy regularized Optimal Transport; potentials, plans and divergences Alberto González Sanz Jean-Michel Loubes Jonathan Niles-Weed OT 43 23 0 15 Jul 2022
An improved central limit theorem and fast convergence rates for entropic transportation costs E. del Barrio Alberto González Sanz Jean-Michel Loubes Jonathan Niles-Weed OT 46 34 0 19 Apr 2022
Distribution Regression with Sliced Wasserstein Kernels Dimitri Meunier Massimiliano Pontil C. Ciliberto OOD 30 16 0 08 Feb 2022
Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein Marco Cuturi Laetitia Meng-Papaxanthos Yingtao Tian Charlotte Bunne Geoff Davis O. Teboul OT 184 105 0 28 Jan 2022
Bernstein-Type Bounds for Beta Distribution Maciej Skorski 96 22 0 06 Jan 2021
Minimax Confidence Intervals for the Sliced Wasserstein Distance Tudor Manole Sivaraman Balakrishnan Larry A. Wasserman 135 36 0 17 Sep 2019
Minimax estimation of smooth densities in Wasserstein distance Jonathan Niles-Weed Quentin Berthet OT 34 38 0 05 Feb 2019
Distribution regression model with a Reproducing Kernel Hilbert Space approach T. T. T. Bui Jean-Michel Loubes Risser Balaresque 41 11 0 27 Jun 2018
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 213 2,147 0 01 Mar 2018
Sliced Wasserstein Distance for Learning Gaussian Mixture Models Soheil Kolouri Gustavo K. Rohde Heiko Hoffmann 43 123 0 15 Nov 2017
A Gaussian Process Regression Model for Distribution Inputs François Bachoc Fabrice Gamboa Jean-Michel Loubes N. Venet 68 52 0 31 Jan 2017
Understanding the 2016 US Presidential Election using ecological inference and distribution regression with census microdata Seth Flaxman Danica J. Sutherland Yu Wang Yee Whye Teh 23 24 0 11 Nov 2016
Uncertain programming model for multi-item solid transportation problem Hasan Dalman 104 64 0 31 May 2016
Sliced Wasserstein Kernels for Probability Distributions Soheil Kolouri Yang Zou Gustavo K. Rohde 39 161 0 10 Nov 2015
Learning Theory for Distribution Regression Z. Szabó Bharath K. Sriperumbudur Barnabás Póczós Arthur Gretton OOD 58 138 0 08 Nov 2014
Fast Distribution To Real Regression Junier B. Oliva Willie Neiswanger Barnabás Póczós J. Schneider Eric Xing 63 45 0 10 Nov 2013
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 209 4,259 0 04 Jun 2013
Distribution-Free Distribution Regression Barnabás Póczós Alessandro Rinaldo Aarti Singh Larry A. Wasserman 82 99 0 01 Feb 2013
Nearly root-n approximation for regression quantile processes S. Portnoy 55 29 0 03 Oct 2012
Learning from Distributions via Support Measure Machines Krikamol Muandet Kenji Fukumizu Francesco Dinuzzo Bernhard Schölkopf 107 198 0 29 Feb 2012
Adaptive Bayesian estimation using a Gaussian random field with inverse Gamma bandwidth Van der Vaart V. Zanten 107 254 0 25 Aug 2009