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2001.09206
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Gaussian-Smooth Optimal Transport: Metric Structure and Statistical Efficiency
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
24 January 2020
Ziv Goldfeld
Kristjan Greenewald
OT
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Papers citing
"Gaussian-Smooth Optimal Transport: Metric Structure and Statistical Efficiency"
30 / 30 papers shown
Differentially Private Wasserstein Barycenters
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Sasidhar Kunapuli
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Edward Chien
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A Smoothing Newton Method for Rank-one Matrix Recovery
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30 Jul 2025
Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
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Aref Einizade
Jhony H. Giraldo
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288
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29 May 2025
Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training
Neural Information Processing Systems (NeurIPS), 2024
Kristjan Greenewald
Yuancheng Yu
Hao Wang
Kai Xu
505
4
0
25 Oct 2024
Bounding adapted Wasserstein metrics
Zhe Liu
Martin Larsson
Jonghwa Park
Johannes Wiesel
OT
268
4
0
31 Jul 2024
Smoothed NPMLEs in nonparametric Poisson mixtures and beyond
Keunwoo Lim
Fang Han
OT
214
1
0
13 Jun 2024
Max-sliced Wasserstein concentration and uniform ratio bounds of empirical measures on RKHS
Ruiyu Han
Cynthia Rush
Johannes Wiesel
315
1
0
21 May 2024
Convergence of the Adapted Smoothed Empirical Measures
Stochastic Processes and their Applications (SPA), 2024
Songyan Hou
257
5
0
26 Jan 2024
Differentially Private Gradient Flow based on the Sliced Wasserstein Distance
Ilana Sebag
Muni Sreenivas Pydi
Jean-Yves Franceschi
Alain Rakotomamonjy
Mike Gartrell
Jamal Atif
Alexandre Allauzen
518
3
0
13 Dec 2023
Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Abdelwahed Khamis
Russell Tsuchida
Mohamed Tarek
V. Rolland
Lars Petersson
OT
514
34
0
08 May 2023
Personalised Federated Learning On Heterogeneous Feature Spaces
A. Rakotomamonjy
Maxime Vono
H. M. Ruiz
L. Ralaivola
FedML
206
13
0
26 Jan 2023
Gromov-Wasserstein Distances: Entropic Regularization, Duality, and Sample Complexity
Annals of Statistics (Ann. Stat.), 2022
Zhengxin Zhang
Ziv Goldfeld
Youssef Mroueh
Bharath K. Sriperumbudur
OT
422
26
0
25 Dec 2022
Asymptotics of smoothed Wasserstein distances in the small noise regime
Neural Information Processing Systems (NeurIPS), 2022
Yunzi Ding
Jonathan Niles-Weed
OT
217
2
0
13 Jun 2022
Statistical inference with regularized optimal transport
Information and Inference A Journal of the IMA (JIII), 2022
Ziv Goldfeld
Kengo Kato
Gabriel Rioux
Ritwik Sadhu
OT
294
45
0
09 May 2022
Limit distribution theory for smooth
p
p
p
-Wasserstein distances
The Annals of Applied Probability (Ann. Appl. Probab.), 2022
Ziv Goldfeld
Kengo Kato
Sloan Nietert
Gabriel Rioux
263
19
0
01 Mar 2022
Nonparametric mixture MLEs under Gaussian-smoothed optimal transport distance
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021
Fang Han
Zhen Miao
Yandi Shen
OT
290
7
0
04 Dec 2021
Order Constraints in Optimal Transport
Fabian Lim
L. Wynter
Shiau Hong Lim
OT
340
4
0
14 Oct 2021
Limit Distribution Theory for the Smooth 1-Wasserstein Distance with Applications
Ritwik Sadhu
Ziv Goldfeld
Kengo Kato
353
10
0
28 Jul 2021
Differentially Private Sliced Wasserstein Distance
A. Rakotomamonjy
L. Ralaivola
219
25
0
05 Jul 2021
Martingale Methods for Sequential Estimation of Convex Functionals and Divergences
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2021
Tudor Manole
Aaditya Ramdas
312
24
0
16 Mar 2021
Fast block-coordinate Frank-Wolfe algorithm for semi-relaxed optimal transport
Takumi Fukunaga
Hiroyuki Kasai
OT
307
6
0
10 Mar 2021
Convergence of Gaussian-smoothed optimal transport distance with sub-gamma distributions and dependent samples
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Yixing Zhang
Xiuyuan Cheng
Galen Reeves
OT
176
11
0
28 Feb 2021
Improving Approximate Optimal Transport Distances using Quantization
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Gaspard Beugnot
Aude Genevay
Kristjan Greenewald
Justin Solomon
OT
MQ
613
11
0
25 Feb 2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
International Conference on Machine Learning (ICML), 2021
Adrien Corenflos
James Thornton
George Deligiannidis
Arnaud Doucet
OT
299
90
0
15 Feb 2021
Two-sample Test with Kernel Projected Wasserstein Distance
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Jie Wang
Rui Gao
Yao Xie
360
23
0
12 Feb 2021
Smooth
p
p
p
-Wasserstein Distance: Structure, Empirical Approximation, and Statistical Applications
International Conference on Machine Learning (ICML), 2021
Sloan Nietert
Ziv Goldfeld
Kengo Kato
270
39
0
11 Jan 2021
A contribution to Optimal Transport on incomparable spaces
Titouan Vayer
OT
397
25
0
09 Nov 2020
Attribute Privacy: Framework and Mechanisms
Conference on Fairness, Accountability and Transparency (FAccT), 2020
Wanrong Zhang
O. Ohrimenko
Rachel Cummings
327
42
0
08 Sep 2020
Limit Distribution for Smooth Total Variation and
χ
2
χ^2
χ
2
-Divergence in High Dimensions
International Symposium on Information Theory (ISIT), 2020
Ziv Goldfeld
Kengo Kato
231
10
0
03 Feb 2020
Asymptotic Guarantees for Generative Modeling Based on the Smooth Wasserstein Distance
Ziv Goldfeld
Kristjan Greenewald
Kengo Kato
396
2
0
03 Feb 2020
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