Distribution Regression with Sliced Wasserstein Kernels

8 February 2022

Papers citing "Distribution Regression with Sliced Wasserstein Kernels"

25 / 25 papers shown

Title
Improved learning theory for kernel distribution regression with two-stage sampling François Bachoc Louis Bethune Alberto González Sanz Jean-Michel Loubes 126 2 0 28 Jan 2025
Robust Kernel-based Distribution Regression Zhan Yu D. Ho Ding-Xuan Zhou OOD 63 11 0 21 Apr 2021
Stochastic Gradient Descent Meets Distribution Regression Nicole Mücke 55 5 0 24 Oct 2020
The Advantage of Conditional Meta-Learning for Biased Regularization and Fine-Tuning Giulia Denevi Massimiliano Pontil C. Ciliberto 86 41 0 25 Aug 2020
Linear Optimal Transport Embedding: Provable Wasserstein classification for certain rigid transformations and perturbations Caroline Moosmüller A. Cloninger OT 119 44 0 20 Aug 2020
Kernel methods through the roof: handling billions of points efficiently Giacomo Meanti Luigi Carratino Lorenzo Rosasco Alessandro Rudi 68 116 0 18 Jun 2020
Statistical and Topological Properties of Sliced Probability Divergences Kimia Nadjahi Alain Durmus Lénaïc Chizat Soheil Kolouri Shahin Shahrampour Umut Simsekli 41 86 0 12 Mar 2020
Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space Q. Mérigot Alex Delalande Frédéric Chazal OT 39 44 0 14 Oct 2019
Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance Kimia Nadjahi Alain Durmus Umut Simsekli Roland Badeau MedIm 56 63 0 11 Jun 2019
Max-Sliced Wasserstein Distance and its use for GANs Ishani Deshpande Yuan-Ting Hu Ruoyu Sun A. Pyrros Nasir Siddiqui Oluwasanmi Koyejo Zhizhen Zhao David A. Forsyth Alex Schwing GAN 40 201 0 11 Apr 2019
Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation Chen-Yu Lee Tanmay Batra M. H. Baig Daniel Ulbricht 127 541 0 10 Mar 2019
Generalized Sliced Wasserstein Distances Soheil Kolouri Kimia Nadjahi Umut Simsekli Roland Badeau Gustavo K. Rohde 50 300 0 01 Feb 2019
Distribution regression model with a Reproducing Kernel Hilbert Space approach T. T. T. Bui Jean-Michel Loubes Risser Balaresque 46 11 0 27 Jun 2018
Generative Modeling using the Sliced Wasserstein Distance Ishani Deshpande Ziyu Zhang Alex Schwing GAN 55 226 0 29 Mar 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 280 8,878 0 25 Aug 2017
Sliced Wasserstein Kernel for Persistence Diagrams Mathieu Carrière Marco Cuturi S. Oudot 56 237 0 11 Jun 2017
A Gaussian Process Regression Model for Distribution Inputs François Bachoc Fabrice Gamboa Jean-Michel Loubes N. Venet 74 52 0 31 Jan 2017
Distributed learning with regularized least squares Shaobo Lin Xin Guo Ding-Xuan Zhou 149 191 0 11 Aug 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
Geodesic Exponential Kernels: When Curvature and Linearity Conflict Aasa Feragen F. Lauze Søren Hauberg BDL 43 144 0 02 Nov 2014
Fast Distribution To Real Regression Junier B. Oliva Willie Neiswanger Barnabás Póczós J. Schneider Eric Xing 63 45 0 10 Nov 2013
Distribution-Free Distribution Regression Barnabás Póczós Alessandro Rinaldo Aarti Singh Larry A. Wasserman 85 99 0 01 Feb 2013
Multiclass Learning with Simplex Coding Youssef Mroueh T. Poggio Lorenzo Rosasco Jean-Jacques E. Slotine 81 52 0 06 Sep 2012