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Revisiting Fixed Support Wasserstein Barycenter: Computational Hardness and Efficient Algorithms.

, , , , and . CoRR, (2020)

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Markovian Sliced Wasserstein Distances: Beyond Independent Projections., , and . CoRR, (2023)Structured Dropout Variational Inference for Bayesian Neural Networks., , , , , and . NeurIPS, page 15188-15202. (2021)Stochastic Multiple Target Sampling Gradient Descent., , , , , and . NeurIPS, (2022)Global-Local Regularization Via Distributional Robustness., , , , , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 7644-7664. PMLR, (2023)Flow-based Alignment Approaches for Probability Measures in Different Spaces., , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 3934-3942. PMLR, (2021)On the Minimax Optimality of the EM Algorithm for Learning Two-Component Mixed Linear Regression., , and . AISTATS, volume 130 of Proceedings of Machine Learning Research, page 1405-1413. PMLR, (2021)On Structured Filtering-Clustering: Global Error Bound and Optimal First-Order Algorithms., , and . AISTATS, volume 151 of Proceedings of Machine Learning Research, page 896-921. PMLR, (2022)Hierarchical Hybrid Sliced Wasserstein: A Scalable Metric for Heterogeneous Joint Distributions., and . CoRR, (2024)On Robust Optimal Transport: Computational Complexity and Barycenter Computation., , , , , and . NeurIPS, page 21947-21959. (2021)Distributional Sliced-Wasserstein and Applications to Generative Modeling., , , and . ICLR, OpenReview.net, (2021)