 Importance Sparsification for Sinkhorn AlgorithmJournal of machine learning research (JMLR), 2023 |
 Markovian Sliced Wasserstein Distances: Beyond Independent ProjectionsNeural Information Processing Systems (NeurIPS), 2023 |
 Hierarchical Sliced Wasserstein DistanceInternational Conference on Learning Representations (ICLR), 2022 |
 Revisiting Sliced Wasserstein on Images: From Vectorization to
ConvolutionNeural Information Processing Systems (NeurIPS), 2022 |
 Global-Local Regularization Via Distributional RobustnessInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 |
 Variational Wasserstein Barycenters with c-Cyclical MonotonicityAAAI Conference on Artificial Intelligence (AAAI), 2021 |
 Fixed Support Tree-Sliced Wasserstein BarycenterInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021 |
 Automatic Text Evaluation through the Lens of Wasserstein BarycentersConference on Empirical Methods in Natural Language Processing (EMNLP), 2021 |
 Decentralized Distributed Optimization for Saddle Point ProblemsOptimization Methods and Software (OMS), 2021 |
 On Robust Optimal Transport: Computational Complexity and Barycenter
ComputationNeural Information Processing Systems (NeurIPS), 2021 |
 Projection Robust Wasserstein BarycentersInternational Conference on Machine Learning (ICML), 2021 |
 Wasserstein barycenters are NP-hard to computeSIAM Journal on Mathematics of Data Science (SIMODS), 2021 |
 First-Order Methods for Convex OptimizationEURO Journal on Computational Optimization (EJCO), 2021 |
 Multi-marginal optimal transport and probabilistic graphical modelsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020 |
 Gradient descent algorithms for Bures-Wasserstein barycentersAnnual Conference Computational Learning Theory (COLT), 2020 |
 On Efficient Multilevel Clustering via Wasserstein DistancesJournal of machine learning research (JMLR), 2019 |
