{"list":"other","total":71,"rows":[{"id":"1602.05629","title":"Communication-Efficient Learning of Deep Networks from Decentralized Data","created":"2016-02-17","cited_by_count":7669},{"id":"1912.04977","title":"Advances and Open Problems in Federated Learning","created":"2019-12-10","cited_by_count":3046},{"id":"1306.0895","title":"Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances","created":"2013-06-04","cited_by_count":2316},{"id":"1911.08731","title":"Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization","created":"2019-11-20","cited_by_count":1247},{"id":"1803.00567","title":"Computational Optimal Transport","created":"2018-03-01","cited_by_count":780},{"id":"1902.00146","title":"Agnostic Federated Learning","created":"2019-02-01","cited_by_count":456},{"id":"1810.08750","title":"Learning Models with Uniform Performance via Distributionally Robust Optimization","created":"2018-10-20","cited_by_count":335},{"id":"2107.06917","title":"A Field Guide to Federated Optimization","created":"2021-07-14","cited_by_count":315},{"id":"1706.00292","title":"Learning Generative Models with Sinkhorn Divergences","created":"2017-06-01","cited_by_count":314},{"id":"1505.05116","title":"Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations","created":"2015-05-19","cited_by_count":291},{"id":"1310.4375","title":"Fast Computation of Wasserstein Barycenters","created":"2013-10-16","cited_by_count":216},{"id":"1806.05500","title":"Statistical Aspects of Wasserstein Distances","created":"2018-06-14","cited_by_count":203},{"id":"1604.02199","title":"Distributionally Robust Stochastic Optimization with Wasserstein Distance","created":"2016-04-08","cited_by_count":185},{"id":"1610.03425","title":"Statistics of Robust Optimization: A Generalized Empirical Likelihood Approach","created":"2016-10-11","cited_by_count":183},{"id":"2010.05893","title":"Large-Scale Methods for Distributionally Robust Optimization","created":"2020-10-12","cited_by_count":179},{"id":"1908.08729","title":"Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning","created":"2019-08-23","cited_by_count":170},{"id":"1509.02237","title":"On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests","created":"2015-09-08","cited_by_count":166},{"id":"1509.09259","title":"Distributionally Robust Logistic Regression","created":"2015-09-30","cited_by_count":126},{"id":"2102.12660","title":"Distributionally Robust Federated Averaging","created":"2021-02-25","cited_by_count":104},{"id":"2006.08907","title":"Robust Federated Learning: The Case of Affine Distribution Shifts","created":"2020-06-16","cited_by_count":102},{"id":"1401.0212","title":"Data-Driven Robust Optimization","created":"2013-12-31","cited_by_count":85},{"id":"1710.10016","title":"Regularization via Mass Transportation","created":"2017-10-27","cited_by_count":81},{"id":"1905.10943","title":"Distributionally Robust Optimization and Generalization in Kernel Methods","created":"2019-05-27","cited_by_count":73},{"id":"2006.08172","title":"Faster Wasserstein Distance Estimation with the Sinkhorn Divergence","created":"2020-06-15","cited_by_count":73},{"id":"2110.14216","title":"What Do We Mean by Generalization in Federated Learning?","created":"2021-10-27","cited_by_count":62},{"id":"2009.04382","title":"Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality","created":"2020-09-09","cited_by_count":49},{"id":"1508.05880","title":"Scalable Bayes via Barycenter in Wasserstein Space","created":"2015-08-24","cited_by_count":44},{"id":"2110.12459","title":"Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis","created":"2021-10-24","cited_by_count":39},{"id":"1708.01955","title":"Wasserstein Dictionary Learning: Optimal Transport-based unsupervised non-linear dictionary learning","created":"2017-08-07","cited_by_count":35},{"id":"2006.02575","title":"Debiased Sinkhorn barycenters","created":"2020-06-03","cited_by_count":34},{"id":"2006.03416","title":"Entropy-Regularized $2$-Wasserstein Distance between Gaussian Measures","created":"2020-06-05","cited_by_count":32},{"id":"2008.12534","title":"Continuous Regularized Wasserstein Barycenters","created":"2020-08-28","cited_by_count":32},{"id":"2104.11720","title":"Entropic Optimal Transport: Convergence of Potentials","created":"2021-04-23","cited_by_count":31},{"id":"1810.02403","title":"Optimal Transport Based Distributionally Robust Optimization: Structural Properties and Iterative Schemes","created":"2018-10-04","cited_by_count":30},{"id":"2101.01100","title":"Wasserstein barycenters are NP-hard to compute","created":"2021-01-04","cited_by_count":28},{"id":"1905.13194","title":"Sinkhorn Barycenters with Free Support via Frank-Wolfe Algorithm","created":"2019-05-30","cited_by_count":27},{"id":"2108.02120","title":"Statistical Analysis of Wasserstein Distributionally Robust Estimators","created":"2021-08-04","cited_by_count":27},{"id":"1811.05527","title":"Semi-dual Regularized Optimal Transport","created":"2018-11-13","cited_by_count":26},{"id":"2106.03670","title":"Stability of Entropic Optimal Transport and Schr\\\"odinger Bridges","created":"2021-06-07","cited_by_count":26},{"id":"1802.04885","title":"Distributionally Robust Mean-Variance Portfolio Selection with Wasserstein Distances","created":"2018-02-13","cited_by_count":25},{"id":"1906.01614","title":"Confidence Regions in Wasserstein Distributionally Robust Estimation","created":"2019-06-04","cited_by_count":24},{"id":"1806.03915","title":"Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters","created":"2018-06-11","cited_by_count":21},{"id":"1805.07594","title":"Generalizing Point Embeddings using the Wasserstein Space of Elliptical Distributions","created":"2018-05-19","cited_by_count":20},{"id":"2102.04397","title":"Entropic Optimal Transport: Geometry and Large Deviations","created":"2021-02-08","cited_by_count":20},{"id":"2104.13326","title":"Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization","created":"2021-04-27","cited_by_count":19},{"id":"1701.06876","title":"Fr\\'echet Means and Procrustes Analysis in Wasserstein Space","created":"2017-01-24","cited_by_count":18},{"id":"2007.09762","title":"A Theory of Multiple-Source Adaptation with Limited Target Labeled Data","created":"2020-07-19","cited_by_count":18},{"id":"1809.08830","title":"Wasserstein Distributionally Robust Kalman Filtering","created":"2018-09-24","cited_by_count":17},{"id":"1805.07194","title":"Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator","created":"2018-05-18","cited_by_count":16},{"id":"1705.07152","title":"Data-driven Optimal Cost Selection for Distributionally Robust Optimization","created":"2017-05-19","cited_by_count":15},{"id":"2106.00322","title":"Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts","created":"2021-06-01","cited_by_count":14},{"id":"2103.06263","title":"Semi-Discrete Optimal Transport: Hardness, Regularization and Numerical Solution","created":"2021-03-10","cited_by_count":13},{"id":"1711.09974","title":"Bootstrap Robust Prescriptive Analytics","created":"2017-11-27","cited_by_count":12},{"id":"1805.10833","title":"Bayesian Learning with Wasserstein Barycenters","created":"2018-05-28","cited_by_count":12},{"id":"1911.03539","title":"Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization","created":"2019-11-08","cited_by_count":11},{"id":"2006.12022","title":"Sensitivity analysis of Wasserstein distributionally robust optimization problems","created":"2020-06-22","cited_by_count":11},{"id":"2104.02748","title":"Communication-Efficient Agnostic Federated Averaging","created":"2021-04-06","cited_by_count":10},{"id":"2112.09959","title":"Mean-Covariance Robust Risk Measurement","created":"2021-12-18","cited_by_count":10},{"id":"1804.08962","title":"Data-driven regularization of Wasserstein barycenters with an application to multivariate density registration","created":"2018-04-24","cited_by_count":8},{"id":"2011.07489","title":"Entropic regularization of Wasserstein distance between infinite-dimensional Gaussian measures and Gaussian processes","created":"2020-11-15","cited_by_count":8},{"id":"2012.06397","title":"Randomised Wasserstein Barycenter Computation: Resampling with Statistical Guarantees","created":"2020-12-11","cited_by_count":8},{"id":"2102.13380","title":"A novel notion of barycenter for probability distributions based on optimal weak mass transport","created":"2021-02-26","cited_by_count":5},{"id":"2105.01706","title":"Sampling From the Wasserstein Barycenter","created":"2021-05-04","cited_by_count":5},{"id":"2203.09607","title":"Learning Distributionally Robust Models at Scale via Composite Optimization","created":"2022-03-17","cited_by_count":5},{"id":"1902.10288","title":"Clustering, factor discovery and optimal transport","created":"2019-02-27","cited_by_count":4},{"id":"1910.14572","title":"Barycenters for the Hellinger--Kantorovich distance over $\\mathbb{R}^d$","created":"2019-10-31","cited_by_count":4},{"id":"2106.06741","title":"Distributionally Robust Optimization with Markovian Data","created":"2021-06-12","cited_by_count":4},{"id":"1901.07693","title":"Optimal Uncertainty Size in Distributionally Robust Inverse Covariance Estimation","created":"2019-01-23","cited_by_count":3},{"id":"2105.00935","title":"Distributionally robust portfolio maximisation and marginal utility pricing in one period financial markets","created":"2021-05-03","cited_by_count":2},{"id":"1404.0145","title":"Network Consensus in the Wasserstein Metric Space of Probability Measures","created":"2014-04-01","cited_by_count":1},{"id":"1703.09754","title":"A canonical barycenter via Wasserstein regularization","created":"2017-03-28","cited_by_count":1}],"next_cursor":null}