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2020 – today
- 2024
[c66]Tianyi Lin, Marco Cuturi, Michael I. Jordan:
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport. AISTATS 2024: 145-153- [c65]Othmane Sebbouh, Marco Cuturi, Gabriel Peyré:
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport. AISTATS 2024: 586-594 - [c64]Yu-Guan Hsieh, James Thornton, Eugène Ndiaye, Michal Klein, Marco Cuturi, Pierre Ablin:
Careful with that Scalpel: Improving Gradient Surgery with an EMA. ICML 2024 - [c63]Zoe Piran, Michal Klein, James Thornton, Marco Cuturi:
Contrasting Multiple Representations with the Multi-Marginal Matching Gap. ICML 2024 - [c62]Nina Vesseron, Marco Cuturi:
On a Neural Implementation of Brenier's Polar Factorization. ICML 2024 - [i69]Yu-Guan Hsieh, James Thornton, Eugène Ndiaye, Michal Klein, Marco Cuturi, Pierre Ablin:
Careful with that Scalpel: Improving Gradient Surgery with an EMA. CoRR abs/2402.02998 (2024) - [i68]Nina Vesseron, Marco Cuturi:
On a Neural Implementation of Brenier's Polar Factorization. CoRR abs/2403.03071 (2024) - [i67]Ben Blum-Smith, Ningyuan Huang, Marco Cuturi, Soledad Villar:
Learning functions on symmetric matrices and point clouds via lightweight invariant features. CoRR abs/2405.08097 (2024) - [i66]Antoine Wehenkel, Juan L. Gamella, Ozan Sener, Jens Behrmann, Guillermo Sapiro, Marco Cuturi, Jörn-Henrik Jacobsen:
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration. CoRR abs/2405.08719 (2024) - [i65]Zoe Piran, Michal Klein, James Thornton, Marco Cuturi:
Contrasting Multiple Representations with the Multi-Marginal Matching Gap. CoRR abs/2405.19532 (2024) - [i64]Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi:
Progressive Entropic Optimal Transport Solvers. CoRR abs/2406.05061 (2024) - [i63]Yu-Guan Hsieh, Cheng-Yu Hsieh, Shih-Ying Yeh, Louis Béthune, Hadipour Ansari, Pavan Kumar Anasosalu Vasu, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Marco Cuturi:
Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions. CoRR abs/2407.06723 (2024) - [i62]Théo Uscidda, Luca Eyring, Karsten Roth, Fabian J. Theis, Zeynep Akata, Marco Cuturi:
Disentangled Representation Learning through Geometry Preservation with the Gromov-Monge Gap. CoRR abs/2407.07829 (2024) - [i61]Michael Kirchhof, James Thornton, Pierre Ablin, Louis Béthune, Eugène Ndiaye, Marco Cuturi:
Sparse Repellency for Shielded Generation in Text-to-image Diffusion Models. CoRR abs/2410.06025 (2024) - [i60]Beomsu Kim, Yu-Guan Hsieh, Michal Klein, Marco Cuturi, Jong Chul Ye, Bahjat Kawar, James Thornton:
Simple ReFlow: Improved Techniques for Fast Flow Models. CoRR abs/2410.07815 (2024) - 2023
- [c61]Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause:
The Schrödinger Bridge between Gaussian Measures has a Closed Form. AISTATS 2023: 5802-5833 - [c60]James Thornton, Marco Cuturi:
Rethinking Initialization of the Sinkhorn Algorithm. AISTATS 2023: 8682-8698 - [c59]Marco Cuturi, Michal Klein, Pierre Ablin:
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps. ICML 2023: 6671-6682 - [c58]Théo Uscidda, Marco Cuturi:
The Monge Gap: A Regularizer to Learn All Transport Maps. ICML 2023: 34709-34733 - [c57]Meyer Scetbon, Michal Klein, Giovanni Palla, Marco Cuturi:
Unbalanced Low-rank Optimal Transport Solvers. NeurIPS 2023 - [i59]Marco Cuturi, Michal Klein, Pierre Ablin:
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps. CoRR abs/2302.04065 (2023) - [i58]Théo Uscidda, Marco Cuturi:
The Monge Gap: A Regularizer to Learn All Transport Maps. CoRR abs/2302.04953 (2023) - [i57]Meyer Scetbon, Michal Klein, Giovanni Palla, Marco Cuturi:
Unbalanced Low-rank Optimal Transport Solvers. CoRR abs/2305.19727 (2023) - [i56]Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugène Ndiaye, Jonathan Niles-Weed, Marco Cuturi:
Learning Costs for Structured Monge Displacements. CoRR abs/2306.11895 (2023) - [i55]Antoine Wehenkel, Jens Behrmann, Andrew C. Miller, Guillermo Sapiro, Ozan Sener, Marco Cuturi, Jörn-Henrik Jacobsen:
Simulation-based Inference for Cardiovascular Models. CoRR abs/2307.13918 (2023) - [i54]Dominik Klein, Théo Uscidda, Fabian J. Theis, Marco Cuturi:
Generative Entropic Neural Optimal Transport To Map Within and Across Spaces. CoRR abs/2310.09254 (2023) - [i53]Tianyi Lin, Marco Cuturi, Michael I. Jordan:
A Specialized Semismooth Newton Method for Kernel-Based Optimal Transport. CoRR abs/2310.14087 (2023) - [i52]Othmane Sebbouh, Marco Cuturi, Gabriel Peyré:
Structured Transforms Across Spaces with Cost-Regularized Optimal Transport. CoRR abs/2311.05788 (2023) - 2022
- [j18]Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan:
On the Complexity of Approximating Multimarginal Optimal Transport. J. Mach. Learn. Res. 23: 65:1-65:43 (2022) - [c56]Othmane Sebbouh, Marco Cuturi, Gabriel Peyré:
Randomized Stochastic Gradient Descent Ascent. AISTATS 2022: 2941-2969 - [c55]Charlotte Bunne, Laetitia Papaxanthos, Andreas Krause, Marco Cuturi:
Proximal Optimal Transport Modeling of Population Dynamics. AISTATS 2022: 6511-6528 - [c54]Yingtao Tian, Marco Cuturi, David Ha:
Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport. ICCC 2022: 324-332 - [c53]Aram-Alexandre Pooladian, Marco Cuturi, Jonathan Niles-Weed:
Debiaser Beware: Pitfalls of Centering Regularized Transport Maps. ICML 2022: 17830-17847 - [c52]Meyer Scetbon, Gabriel Peyré, Marco Cuturi:
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs. ICML 2022: 19347-19365 - [c51]Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert:
Efficient and Modular Implicit Differentiation. NeurIPS 2022 - [c50]Charlotte Bunne, Andreas Krause, Marco Cuturi:
Supervised Training of Conditional Monge Maps. NeurIPS 2022 - [c49]Meyer Scetbon, Marco Cuturi:
Low-rank Optimal Transport: Approximation, Statistics and Debiasing. NeurIPS 2022 - [i51]Marco Cuturi, Laetitia Meng-Papaxanthos, Yingtao Tian, Charlotte Bunne, Geoff Davis, Olivier Teboul:
Optimal Transport Tools (OTT): A JAX Toolbox for all things Wasserstein. CoRR abs/2201.12324 (2022) - [i50]Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause:
Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges. CoRR abs/2202.05722 (2022) - [i49]Hicham Janati, Marco Cuturi, Alexandre Gramfort:
Averaging Spatio-temporal Signals using Optimal Transport and Soft Alignments. CoRR abs/2203.05813 (2022) - [i48]Yingtao Tian, Marco Cuturi, David Ha:
Simultaneous Multiple-Prompt Guided Generation Using Differentiable Optimal Transport. CoRR abs/2204.08472 (2022) - [i47]Meyer Scetbon, Marco Cuturi:
Low-rank Optimal Transport: Approximation, Statistics and Debiasing. CoRR abs/2205.12365 (2022) - [i46]James Thornton, Marco Cuturi:
Rethinking Initialization of the Sinkhorn Algorithm. CoRR abs/2206.07630 (2022) - [i45]Charlotte Bunne, Andreas Krause, Marco Cuturi:
Supervised Training of Conditional Monge Maps. CoRR abs/2206.14262 (2022) - 2021
- [j17]Matthieu Heitz
, Nicolas Bonneel, David Coeurjolly, Marco Cuturi, Gabriel Peyré:
Ground Metric Learning on Graphs. J. Math. Imaging Vis. 63(1): 89-107 (2021) - [c48]Tianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan:
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification. AISTATS 2021: 262-270 - [c47]Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi:
Equitable and Optimal Transport with Multiple Agents. AISTATS 2021: 2035-2043 - [c46]Meyer Scetbon, Marco Cuturi, Gabriel Peyré:
Low-Rank Sinkhorn Factorization. ICML 2021: 9344-9354 - [i44]Meyer Scetbon, Marco Cuturi, Gabriel Peyré:
Low-Rank Sinkhorn Factorization. CoRR abs/2103.04737 (2021) - [i43]Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert:
Efficient and Modular Implicit Differentiation. CoRR abs/2105.15183 (2021) - [i42]Meyer Scetbon, Gabriel Peyré, Marco Cuturi:
Linear-Time Gromov Wasserstein Distances using Low Rank Couplings and Costs. CoRR abs/2106.01128 (2021) - [i41]Charlotte Bunne, Laetitia Meng-Papaxanthos, Andreas Krause, Marco Cuturi:
JKOnet: Proximal Optimal Transport Modeling of Population Dynamics. CoRR abs/2106.06345 (2021) - [i40]Othmane Sebbouh, Marco Cuturi, Gabriel Peyré:
Randomized Stochastic Gradient Descent Ascent. CoRR abs/2111.13162 (2021) - 2020
- [j16]Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort:
Multi-subject MEG/EEG source imaging with sparse multi-task regression. NeuroImage 220: 116847 (2020) - [c45]François-Pierre Paty, Alexandre d'Aspremont, Marco Cuturi:
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport. AISTATS 2020: 1222-1232 - [c44]Hicham Janati, Marco Cuturi, Alexandre Gramfort:
Spatio-temporal alignments: Optimal transport through space and time. AISTATS 2020: 1695-1704 - [c43]Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly:
Precision-Recall Curves Using Information Divergence Frontiers. AISTATS 2020: 2550-2559 - [c42]Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert:
Supervised Quantile Normalization for Low Rank Matrix Factorization. ICML 2020: 2269-2279 - [c41]Hicham Janati, Marco Cuturi, Alexandre Gramfort:
Debiased Sinkhorn barycenters. ICML 2020: 4692-4701 - [c40]Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi:
Missing Data Imputation using Optimal Transport. ICML 2020: 7130-7140 - [c39]François-Pierre Paty, Marco Cuturi:
Regularized Optimal Transport is Ground Cost Adversarial. ICML 2020: 7532-7542 - [c38]Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach:
Learning with Differentiable Pertubed Optimizers. NeurIPS 2020 - [c37]Hicham Janati, Boris Muzellec, Gabriel Peyré, Marco Cuturi:
Entropic Optimal Transport between Unbalanced Gaussian Measures has a Closed Form. NeurIPS 2020 - [c36]Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan:
Projection Robust Wasserstein Distance and Riemannian Optimization. NeurIPS 2020 - [c35]Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan:
Fixed-Support Wasserstein Barycenters: Computational Hardness and Fast Algorithm. NeurIPS 2020 - [c34]Meyer Scetbon, Marco Cuturi:
Linear Time Sinkhorn Divergences using Positive Features. NeurIPS 2020 - [i39]Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima:
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces. CoRR abs/2002.01615 (2020) - [i38]Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert:
Supervised Quantile Normalization for Low-rank Matrix Approximation. CoRR abs/2002.03229 (2020) - [i37]Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi:
Missing Data Imputation using Optimal Transport. CoRR abs/2002.03860 (2020) - [i36]François-Pierre Paty, Marco Cuturi:
Regularized Optimal Transport is Ground Cost Adversarial. CoRR abs/2002.03967 (2020) - [i35]Tianyi Lin, Nhat Ho, Xi Chen, Marco Cuturi, Michael I. Jordan:
Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms. CoRR abs/2002.04783 (2020) - [i34]Quentin Berthet, Mathieu Blondel, Olivier Teboul, Marco Cuturi, Jean-Philippe Vert, Francis R. Bach:
Learning with Differentiable Perturbed Optimizers. CoRR abs/2002.08676 (2020) - [i33]Marco Cuturi, Olivier Teboul, Jean-Philippe Vert:
Noisy Adaptive Group Testing using Bayesian Sequential Experimental Design. CoRR abs/2004.12508 (2020) - [i32]Hicham Janati, Marco Cuturi, Alexandre Gramfort:
Debiased Sinkhorn barycenters. CoRR abs/2006.02575 (2020) - [i31]Meyer Scetbon, Marco Cuturi:
Linear Time Sinkhorn Divergences using Positive Features. CoRR abs/2006.07057 (2020) - [i30]Meyer Scetbon, Laurent Meunier, Jamal Atif, Marco Cuturi:
Handling Multiple Costs in Optimal Transport: Strong Duality and Efficient Computation. CoRR abs/2006.07260 (2020) - [i29]Tianyi Lin, Chenyou Fan, Nhat Ho, Marco Cuturi, Michael I. Jordan:
Projection Robust Wasserstein Distance and Riemannian Optimization. CoRR abs/2006.07458 (2020) - [i28]Tianyi Lin, Zeyu Zheng, Elynn Y. Chen, Marco Cuturi, Michael I. Jordan:
On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification. CoRR abs/2006.12301 (2020)
2010 – 2019
- 2019
- [j15]Gabriel Peyré, Marco Cuturi:
Computational Optimal Transport. Found. Trends Mach. Learn. 11(5-6): 355-607 (2019) - [j14]Shun-ichi Amari, Ryo Karakida, Masafumi Oizumi, Marco Cuturi:
Information Geometry for Regularized Optimal Transport and Barycenters of Patterns. Neural Comput. 31(5): 827-848 (2019) - [c33]Hicham Janati, Marco Cuturi, Alexandre Gramfort:
Wasserstein regularization for sparse multi-task regression. AISTATS 2019: 1407-1416 - [c32]Aude Genevay, Lénaïc Chizat, Francis R. Bach, Marco Cuturi, Gabriel Peyré:
Sample Complexity of Sinkhorn Divergences. AISTATS 2019: 1574-1583 - [c31]Jean Alaux, Edouard Grave, Marco Cuturi, Armand Joulin:
Unsupervised Hyper-alignment for Multilingual Word Embeddings. ICLR (Poster) 2019 - [c30]Gwendoline de Bie, Gabriel Peyré, Marco Cuturi:
Stochastic Deep Networks. ICML 2019: 1556-1565 - [c29]François-Pierre Paty, Marco Cuturi:
Subspace Robust Wasserstein Distances. ICML 2019: 5072-5081 - [c28]Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort:
Group Level MEG/EEG Source Imaging via Optimal Transport: Minimum Wasserstein Estimates. IPMI 2019: 743-754 - [c27]Marco Cuturi, Olivier Teboul, Jean-Philippe Vert:
Differentiable Ranking and Sorting using Optimal Transport. NeurIPS 2019: 6858-6868 - [c26]Boris Muzellec, Marco Cuturi:
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections. NeurIPS 2019: 6914-6925 - [c25]Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi:
Tree-Sliced Variants of Wasserstein Distances. NeurIPS 2019: 12283-12294 - [i27]François-Pierre Paty, Marco Cuturi:
Subspace Robust Wasserstein distances. CoRR abs/1901.08949 (2019) - [i26]Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi:
Tree-Sliced Approximation of Wasserstein Distances. CoRR abs/1902.00342 (2019) - [i25]Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort:
Group level MEG/EEG source imaging via optimal transport: minimum Wasserstein estimates. CoRR abs/1902.04812 (2019) - [i24]Boris Muzellec, Marco Cuturi:
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections. CoRR abs/1905.10099 (2019) - [i23]Josip Djolonga, Mario Lucic, Marco Cuturi, Olivier Bachem, Olivier Bousquet, Sylvain Gelly:
Evaluating Generative Models Using Divergence Frontiers. CoRR abs/1905.10768 (2019) - [i22]François-Pierre Paty, Alexandre d'Aspremont, Marco Cuturi:
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport. CoRR abs/1905.10812 (2019) - [i21]Marco Cuturi, Olivier Teboul, Jean-Philippe Vert:
Differentiable Sorting using Optimal Transport: The Sinkhorn CDF and Quantile Operator. CoRR abs/1905.11885 (2019) - [i20]Gabriel Dulac-Arnold, Neil Zeghidour, Marco Cuturi, Lucas Beyer, Jean-Philippe Vert:
Deep multi-class learning from label proportions. CoRR abs/1905.12909 (2019) - [i19]Tianyi Lin, Nhat Ho, Marco Cuturi, Michael I. Jordan:
On the Complexity of Approximating Multimarginal Optimal Transport. CoRR abs/1910.00152 (2019) - [i18]Hicham Janati, Thomas Bazeille, Bertrand Thirion, Marco Cuturi, Alexandre Gramfort:
Multi-subject MEG/EEG source imaging with sparse multi-task regression. CoRR abs/1910.01914 (2019) - [i17]Hicham Janati, Marco Cuturi, Alexandre Gramfort:
Spatio-Temporal Alignments: Optimal transport through space and time. CoRR abs/1910.03860 (2019) - [i16]Matthieu Heitz, Nicolas Bonneel, David Coeurjolly, Marco Cuturi, Gabriel Peyré:
Ground Metric Learning on Graphs. CoRR abs/1911.03117 (2019) - 2018
- [j13]Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy:
Wasserstein discriminant analysis. Mach. Learn. 107(12): 1923-1945 (2018) - [j12]Morgan A. Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Maurice Ngolè Mboula, David Coeurjolly, Marco Cuturi, Gabriel Peyré, Jean-Luc Starck:
Wasserstein Dictionary Learning: Optimal Transport-Based Unsupervised Nonlinear Dictionary Learning. SIAM J. Imaging Sci. 11(1): 643-678 (2018) - [j11]Marco Cuturi, Gabriel Peyré:
Semidual Regularized Optimal Transport. SIAM Rev. 60(4): 941-965 (2018) - [j10]Elsa Cazelles, Vivien Seguy, Jérémie Bigot, Marco Cuturi, Nicolas Papadakis:
Geodesic PCA versus Log-PCA of Histograms in the Wasserstein Space. SIAM J. Sci. Comput. 40(2) (2018) - [c24]Aude Genevay, Gabriel Peyré, Marco Cuturi:
Learning Generative Models with Sinkhorn Divergences. AISTATS 2018: 1608-1617 - [c23]Théo Lacombe, Marco Cuturi, Steve Oudot:
Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport. NeurIPS 2018: 9792-9802 - [c22]Boris Muzellec, Marco Cuturi:
Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions. NeurIPS 2018: 10258-10269 - [i15]Boris Muzellec, Marco Cuturi:
Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions. CoRR abs/1805.07594 (2018) - [i14]Hicham Janati, Marco Cuturi, Alexandre Gramfort:
Wasserstein regularization for sparse multi-task regression. CoRR abs/1805.07833 (2018) - [i13]Théo Lacombe, Marco Cuturi, Steve Oudot:
Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport. CoRR abs/1805.08331 (2018) - [i12]Jean Alaux, Edouard Grave, Marco Cuturi, Armand Joulin:
Unsupervised Hyperalignment for Multilingual Word Embeddings. CoRR abs/1811.01124 (2018) - [i11]Marco Cuturi, Gabriel Peyré:
Semi-dual Regularized Optimal Transport. CoRR abs/1811.05527 (2018) - [i10]Gwendoline de Bie, Gabriel Peyré, Marco Cuturi:
Stochastic Deep Networks. CoRR abs/1811.07429 (2018) - 2017
- [j9]Aaditya Ramdas, Nicolás García Trillos, Marco Cuturi:
On Wasserstein Two-Sample Testing and Related Families of Nonparametric Tests. Entropy 19(2): 47 (2017) - [c21]Mathieu Carrière, Marco Cuturi, Steve Oudot:
Sliced Wasserstein Kernel for Persistence Diagrams. ICML 2017: 664-673 - [c20]Marco Cuturi, Mathieu Blondel:
Soft-DTW: a Differentiable Loss Function for Time-Series. ICML 2017: 894-903 - [e1]Oren Anava, Azadeh Khaleghi, Marco Cuturi, Vitaly Kuznetsov, Alexander Rakhlin:
Proceedings of the NIPS 2016 Time Series Workshop, co-located with the 30th Annual Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain, December 9, 2016. JMLR Workshop and Conference Proceedings 55, JMLR.org 2017 [contents] - [i9]Mathieu Carrière, Marco Cuturi, Steve Oudot:
Sliced Wasserstein Kernel for Persistence Diagrams. CoRR abs/1706.03358 (2017) - [i8]Morgan A. Schmitz, Matthieu Heitz, Nicolas Bonneel, Fred Maurice Ngolè Mboula, David Coeurjolly, Marco Cuturi, Gabriel Peyré, Jean-Luc Starck:
Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning. CoRR abs/1708.01955 (2017) - 2016
- [j8]Marco Cuturi, Gabriel Peyré:
A Smoothed Dual Approach for Variational Wasserstein Problems. SIAM J. Imaging Sci. 9(1): 320-343 (2016) - [j7]Nicolas Bonneel, Gabriel Peyré, Marco Cuturi:
Wasserstein barycentric coordinates: histogram regression using optimal transport. ACM Trans. Graph. 35(4): 71:1-71:10 (2016) - [c19]Antoine Rolet, Marco Cuturi, Gabriel Peyré:
Fast Dictionary Learning with a Smoothed Wasserstein Loss. AISTATS 2016: 630-638 - [c18]Gabriel Peyré, Marco Cuturi, Justin Solomon:
Gromov-Wasserstein Averaging of Kernel and Distance Matrices. ICML 2016: 2664-2672 - [c17]Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis R. Bach:
Stochastic Optimization for Large-scale Optimal Transport. NIPS 2016: 3432-3440 - [c16]Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi:
Wasserstein Training of Restricted Boltzmann Machines. NIPS 2016: 3711-3719 - [i7]Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis R. Bach:
Stochastic Optimization for Large-scale Optimal Transport. CoRR abs/1605.08527 (2016) - [i6]Rémi Flamary, Marco Cuturi, Nicolas Courty, Alain Rakotomamonjy:
Wasserstein Discriminant Analysis. CoRR abs/1608.08063 (2016) - 2015
- [j6]Tam Le, Marco Cuturi:
Adaptive Euclidean maps for histograms: generalized Aitchison embeddings. Mach. Learn. 99(2): 169-187 (2015) - [j5]Jean-David Benamou, Guillaume Carlier, Marco Cuturi, Luca Nenna, Gabriel Peyré:
Iterative Bregman Projections for Regularized Transportation Problems. SIAM J. Sci. Comput. 37(2) (2015) - [j4]Justin Solomon, Fernando de Goes, Gabriel Peyré, Marco Cuturi, Adrian Butscher, Andy Nguyen, Tao Du, Leonidas J. Guibas:
Convolutional wasserstein distances: efficient optimal transportation on geometric domains. ACM Trans. Graph. 34(4): 66:1-66:11 (2015) - [c15]Tam Le, Marco Cuturi:
Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations. ICML 2015: 2002-2011 - [c14]Alexandre Gramfort, Gabriel Peyré, Marco Cuturi:
Fast Optimal Transport Averaging of Neuroimaging Data. IPMI 2015: 261-272 - [c13]Vivien Seguy, Marco Cuturi:
Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric. NIPS 2015: 3312-3320 - [i5]Alexandre Gramfort, Gabriel Peyré, Marco Cuturi:
Fast Optimal Transport Averaging of Neuroimaging Data. CoRR abs/1503.08596 (2015) - [i4]Grégoire Montavon, Klaus-Robert Müller, Marco Cuturi:
Wasserstein Training of Boltzmann Machines. CoRR abs/1507.01972 (2015) - 2014
- [j3]Marco Cuturi, David Avis:
Ground metric learning. J. Mach. Learn. Res. 15(1): 533-564 (2014) - [c12]Marco Cuturi, Arnaud Doucet:
Fast Computation of Wasserstein Barycenters. ICML 2014: 685-693 - 2013
- [c11]Tam Le, Marco Cuturi:
Generalized Aitchison Embeddings for Histograms. ACML 2013: 293-308 - [c10]Marco Cuturi, Alexandre d'Aspremont:
Mean Reversion with a Variance Threshold. ICML (3) 2013: 271-279 - [c9]Marco Cuturi:
Sinkhorn Distances: Lightspeed Computation of Optimal Transport. NIPS 2013: 2292-2300 - 2011
- [c8]Marco Cuturi:
Fast Global Alignment Kernels. ICML 2011: 929-936 - [c7]Kilho Shin, Marco Cuturi, Tetsuji Kuboyama:
Mapping kernels for trees. ICML 2011: 961-968 - [d1]Marco Cuturi:
PEMS-SF. UCI Machine Learning Repository, 2011
- [i3]Marco Cuturi, David Avis:
Ground Metric Learning. CoRR abs/1110.2306 (2011)
2000 – 2009
- 2009
- [c6]Marco Cuturi, Jean-Philippe Vert, Alexandre d'Aspremont:
White Functionals for Anomaly Detection in Dynamical Systems. NIPS 2009: 432-440 - 2007
- [c5]Marco Cuturi, Jean-Philippe Vert, Øystein Birkenes, Tomoko Matsui:
A Kernel for Time Series Based on Global Alignments. ICASSP (2) 2007: 413-416 - [c4]Marco Cuturi:
Permanents, Transport Polytopes and Positive Definite Kernels on Histograms. IJCAI 2007: 732-737 - 2006
- [c3]Marco Cuturi, Kenji Fukumizu:
Kernels on Structured Objects Through Nested Histograms. NIPS 2006: 329-336 - [c2]Masaki Naito, Kazunori Matsumoto, Masami Shishibori, Kenji Kita, Marco Cuturi, Tomoko Matsui, Shin'ichi Satoh, Keiichiro Hoashi, Fumiaki Sugaya, Yasuyuki Nakajima:
Shot Boundary Detection and High-Level Feature Extraction Experiments for TRECVID 2006. TRECVID 2006 - [i2]Marco Cuturi, Jean-Philippe Vert, Øystein Birkenes, Tomoko Matsui:
A kernel for time series based on global alignments. CoRR abs/cs/0610033 (2006) - 2005
- [j2]Marco Cuturi, Kenji Fukumizu, Jean-Philippe Vert:
Semigroup Kernels on Measures. J. Mach. Learn. Res. 6: 1169-1198 (2005) - [j1]Marco Cuturi, Jean-Philippe Vert:
The context-tree kernel for strings. Neural Networks 18(8): 1111-1123 (2005) - [i1]Marco Cuturi, Kenji Fukumizu:
Multiresolution Kernels. CoRR abs/cs/0507033 (2005) - 2004
- [c1]Marco Cuturi, Jean-Philippe Vert:
Semigroup Kernels on Finite Sets. NIPS 2004: 329-336
Coauthor Index
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