Convergence and Concentration of Empirical Measures under Wasserstein Distance in Unbounded Functional Spaces

27 April 2018

Papers citing "Convergence and Concentration of Empirical Measures under Wasserstein Distance in Unbounded Functional Spaces"

28 / 78 papers shown

Title
A new approach to posterior contraction rates via Wasserstein dynamics Emanuele Dolera Stefano Favaro E. Mainini 16 1 0 29 Nov 2020
Asymptotics of Discrete Schrödinger Bridges via Chaos Decomposition Zaïd Harchaoui Lang Liu Soumik Pal 10 3 0 17 Nov 2020
A contribution to Optimal Transport on incomparable spaces Titouan Vayer OT 25 20 0 09 Nov 2020
Evaluating Model Robustness and Stability to Dataset Shift Adarsh Subbaswamy R. Adams Suchi Saria OOD 24 9 0 28 Oct 2020
Statistical guarantees for generative models without domination Nicolas Schreuder Victor-Emmanuel Brunel A. Dalalyan GAN 65 34 0 19 Oct 2020
Distributionally Robust Losses for Latent Covariate Mixtures John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 18 79 0 28 Jul 2020
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification Tianyi Lin Zeyu Zheng Elynn Y. Chen Marco Cuturi Michael I. Jordan OT 12 57 0 22 Jun 2020
Projection Robust Wasserstein Distance and Riemannian Optimization Tianyi Lin Chenyou Fan Nhat Ho Marco Cuturi Michael I. Jordan 14 68 0 12 Jun 2020
High-Dimensional Non-Parametric Density Estimation in Mixed Smooth Sobolev Spaces Liang Ding Lu Zou Wei Cao Shahin Shahrampour Rui Tuo 9 3 0 05 Jun 2020
A Universal Approximation Theorem of Deep Neural Networks for Expressing Probability Distributions Yulong Lu Jianfeng Lu 18 19 0 19 Apr 2020
Non-asymptotic bounds for stochastic optimization with biased noisy gradient oracles Nirav Bhavsar Prashanth L.A. 14 11 0 26 Feb 2020
Local continuity of log-concave projection, with applications to estimation under model misspecification Rina Foygel Barber R. Samworth 6 6 0 14 Feb 2020
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance Ziv Goldfeld Kristjan Greenewald Kengo Kato 49 2 0 03 Feb 2020
Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs Jeff Calder Nicolas García Trillos 35 40 0 29 Oct 2019
Minimax Confidence Intervals for the Sliced Wasserstein Distance Tudor Manole Sivaraman Balakrishnan Larry A. Wasserman 13 35 0 17 Sep 2019
Estimation of Wasserstein distances in the Spiked Transport Model Jonathan Niles-Weed Philippe Rigollet 25 102 0 16 Sep 2019
Bootstrapping Networks with Latent Space Structure Keith D. Levin Elizaveta Levina 19 30 0 25 Jul 2019
Distributionally Robust Optimization and Generalization in Kernel Methods Matthew Staib Stefanie Jegelka 31 128 0 27 May 2019
A Wasserstein distance approach for concentration of empirical risk estimates A. PrashanthL. S. Bhat 23 20 0 27 Feb 2019
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses Ananya Uppal Shashank Singh Barnabás Póczós 30 52 0 09 Feb 2019
Learning finite-dimensional coding schemes with nonlinear reconstruction maps Jaeho Lee Maxim Raginsky 23 9 0 23 Dec 2018
Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds Tingran Gao S. Asoodeh Yi Huang James A. Evans 9 6 0 06 Sep 2018
Consistent polynomial-time unseeded graph matching for Lipschitz graphons Yuan Zhang 14 3 0 29 Jul 2018
Unseeded low-rank graph matching by transform-based unsupervised point registration Yuan Zhang 24 6 0 12 Jul 2018
Nonparametric Density Estimation under Adversarial Losses Shashank Singh Ananya Uppal Boyue Li Chun-Liang Li Manzil Zaheer Barnabás Póczós GAN 23 55 0 22 May 2018
Network Representation Using Graph Root Distributions Jing Lei 51 31 0 27 Feb 2018
Minimax Distribution Estimation in Wasserstein Distance Shashank Singh Barnabás Póczós 26 0 0 24 Feb 2018
Relaxed Wasserstein with Applications to GANs Xin Guo Johnny Hong Tianyi Lin Nan Yang GAN 30 35 0 19 May 2017