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1812.05189
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Massively scalable Sinkhorn distances via the Nyström method
12 December 2018
Jason M. Altschuler
Francis R. Bach
Alessandro Rudi
Jonathan Niles-Weed
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Papers citing
"Massively scalable Sinkhorn distances via the Nyström method"
44 / 44 papers shown
Faster Computation of Entropic Optimal Transport via Stable Low Frequency Modes
Reda Chhaibi
Serge Gratton
Samuel Vaiter
OT
145
0
0
23 May 2025
Spherical Tree-Sliced Wasserstein Distance
International Conference on Learning Representations (ICLR), 2025
Hoang V. Tran
Thanh T. Chu
K. Nguyen
Trang Pham
Tam Le
Trung Quoc Nguyen
OT
294
6
0
14 Mar 2025
Low-Rank Thinning
Annabelle Michael Carrell
Albert Gong
Abhishek Shetty
Raaz Dwivedi
Lester W. Mackey
459
0
0
17 Feb 2025
SAVA: Scalable Learning-Agnostic Data Valuation
Samuel Kessler
Tam Le
Vu Nguyen
TDI
479
1
0
03 Jun 2024
Safe Screening for Unbalanced Optimal Transport
Xun Su
Zhongxi Fang
Hiroyuki Kasai
OT
252
0
0
01 Jul 2023
Fast Computation of Optimal Transport via Entropy-Regularized Extragradient Methods
SIAM Journal on Optimization (SIOPT), 2023
Gen Li
Yanxi Chen
Yu Huang
Yuejie Chi
H. Vincent Poor
Yuxin Chen
OT
218
5
0
30 Jan 2023
Geometric Sparse Coding in Wasserstein Space
M. Mueller
Shuchin Aeron
James M. Murphy
Abiy Tasissa
168
4
0
21 Oct 2022
Rethinking Initialization of the Sinkhorn Algorithm
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
James Thornton
Marco Cuturi
OT
232
14
0
15 Jun 2022
Hilbert Curve Projection Distance for Distribution Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022
Tao Li
Cheng Meng
Hongteng Xu
Jun Yu
376
16
0
30 May 2022
Provably Efficient Kernelized Q-Learning
Shuang Liu
H. Su
MLT
271
4
0
21 Apr 2022
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
Keaton Hamm
Nick Henscheid
Shujie Kang
243
21
0
13 Apr 2022
Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR
Dheeraj Baby
Hilaf Hasson
Yuyang Wang
185
4
0
22 Nov 2021
Approximating Optimal Transport via Low-rank and Sparse Factorization
Weijie Liu
Chao Zhang
Nenggan Zheng
Hui Qian
OT
75
3
0
12 Nov 2021
Order Constraints in Optimal Transport
Fabian Lim
L. Wynter
Shiau Hong Lim
OT
227
4
0
14 Oct 2021
Entropic estimation of optimal transport maps
Aram-Alexandre Pooladian
Jonathan Niles-Weed
OT
257
128
0
24 Sep 2021
Deep Networks Provably Classify Data on Curves
Neural Information Processing Systems (NeurIPS), 2021
Tingran Wang
Sam Buchanan
D. Gilboa
John N. Wright
242
9
0
29 Jul 2021
Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
International Conference on Machine Learning (ICML), 2021
Johannes Klicpera
Marten Lienen
Stephan Günnemann
OT
201
14
0
14 Jul 2021
PSD Representations for Effective Probability Models
Neural Information Processing Systems (NeurIPS), 2021
Alessandro Rudi
C. Ciliberto
TPM
280
23
0
30 Jun 2021
Low Budget Active Learning via Wasserstein Distance: An Integer Programming Approach
International Conference on Learning Representations (ICLR), 2021
Rafid Mahmood
Sanja Fidler
M. Law
246
40
0
05 Jun 2021
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs
International Conference on Machine Learning (ICML), 2021
M. Scetbon
Gabriel Peyré
Marco Cuturi
OT
200
69
0
02 Jun 2021
Low-Rank Sinkhorn Factorization
International Conference on Machine Learning (ICML), 2021
M. Scetbon
Marco Cuturi
Gabriel Peyré
172
67
0
08 Mar 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
230
87
0
15 Feb 2021
On Robust Optimal Transport: Computational Complexity and Barycenter Computation
Neural Information Processing Systems (NeurIPS), 2021
Khang Le
Huy Le Nguyen
Quang H. Nguyen
Tung Pham
Hung Bui
Nhat Ho
OT
199
41
0
13 Feb 2021
Making transport more robust and interpretable by moving data through a small number of anchor points
International Conference on Machine Learning (ICML), 2020
Chi-Heng Lin
Mehdi Azabou
Eva L. Dyer
OT
OOD
375
24
0
21 Dec 2020
A contribution to Optimal Transport on incomparable spaces
Titouan Vayer
OT
295
22
0
09 Nov 2020
Sufficient dimension reduction for classification using principal optimal transport direction
Neural Information Processing Systems (NeurIPS), 2020
Cheng Meng
Jun Yu
Jingyi Zhang
Ping Ma
Wenxuan Zhong
330
21
0
19 Oct 2020
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation
Neural Information Processing Systems (NeurIPS), 2020
Thibault Séjourné
François-Xavier Vialard
Gabriel Peyré
OT
333
85
0
09 Sep 2020
Polynomial-time algorithms for Multimarginal Optimal Transport problems with structure
Mathematical programming (Math. Program.), 2020
Jason M. Altschuler
Enric Boix-Adserà
321
34
0
07 Aug 2020
Convergence of Sparse Variational Inference in Gaussian Processes Regression
Journal of machine learning research (JMLR), 2020
David R. Burt
C. Rasmussen
Mark van der Wilk
224
92
0
01 Aug 2020
Multi-marginal optimal transport and probabilistic graphical models
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020
Isabel Haasler
Rahul Singh
Qinsheng Zhang
Johan Karlsson
Yongxin Chen
OT
159
47
0
25 Jun 2020
Linear Time Sinkhorn Divergences using Positive Features
Neural Information Processing Systems (NeurIPS), 2020
M. Scetbon
Marco Cuturi
205
27
0
12 Jun 2020
Fast Unbalanced Optimal Transport on a Tree
Ryoma Sato
M. Yamada
H. Kashima
OT
235
29
0
04 Jun 2020
CO-Optimal Transport
Neural Information Processing Systems (NeurIPS), 2020
Ivegen Redko
Titouan Vayer
Rémi Flamary
Nicolas Courty
OT
233
73
0
10 Feb 2020
Statistical Optimal Transport posed as Learning Kernel Embedding
Neural Information Processing Systems (NeurIPS), 2020
SakethaNath Jagarlapudi
Pratik Jawanpuria
OT
294
17
0
08 Feb 2020
Ground Metric Learning on Graphs
Journal of Mathematical Imaging and Vision (JMIV), 2019
Matthieu Heitz
Nicolas Bonneel
D. Coeurjolly
Marco Cuturi
Gabriel Peyré
OT
283
22
0
08 Nov 2019
Importance Sampling via Local Sensitivity
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Anant Raj
Cameron Musco
Lester W. Mackey
246
7
0
04 Nov 2019
Balancing Gaussian vectors in high dimension
Annual Conference Computational Learning Theory (COLT), 2019
Paxton Turner
Raghu Meka
Philippe Rigollet
210
30
0
30 Oct 2019
Sinkhorn Divergences for Unbalanced Optimal Transport
Thibault Séjourné
Jean Feydy
Franccois-Xavier Vialard
A. Trouvé
Gabriel Peyré
OT
334
82
0
28 Oct 2019
Tree-Wasserstein Barycenter for Large-Scale Multilevel Clustering and Scalable Bayes
Tam Le
Viet Huynh
Nhat Ho
Dinh Q. Phung
M. Yamada
210
6
0
10 Oct 2019
Nyström landmark sampling and regularized Christoffel functions
Machine-mediated learning (ML), 2019
Michaël Fanuel
J. Schreurs
Johan A. K. Suykens
289
14
0
29 May 2019
Efficient online learning with kernels for adversarial large scale problems
Neural Information Processing Systems (NeurIPS), 2019
Rémi Jézéquel
Pierre Gaillard
Alessandro Rudi
184
15
0
26 Feb 2019
Tree-Sliced Variants of Wasserstein Distances
Neural Information Processing Systems (NeurIPS), 2019
Tam Le
M. Yamada
Kenji Fukumizu
Marco Cuturi
OT
332
92
0
01 Feb 2019
Subspace Robust Wasserstein Distances
François-Pierre Paty
Marco Cuturi
402
170
0
25 Jan 2019
Uncoupled isotonic regression via minimum Wasserstein deconvolution
Information and Inference A Journal of the IMA (JIII), 2018
Philippe Rigollet
Jonathan Niles-Weed
176
69
0
27 Jun 2018
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