{"list":"other","total":54,"rows":[{"id":"1306.0895","title":"Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances","created":"2013-06-04","cited_by_count":2316},{"id":"1704.00028","title":"Improved Training of Wasserstein GANs","created":"2017-03-31","cited_by_count":2235},{"id":"1803.00567","title":"Computational Optimal Transport","created":"2018-03-01","cited_by_count":780},{"id":"1405.4980","title":"Convex Optimization: Algorithms and Complexity","created":"2014-05-20","cited_by_count":575},{"id":"1507.00504","title":"Optimal Transport for Domain Adaptation","created":"2015-07-02","cited_by_count":463},{"id":"1602.02068","title":"From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification","created":"2016-02-05","cited_by_count":341},{"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":"1705.09634","title":"Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration","created":"2017-05-26","cited_by_count":223},{"id":"1605.08527","title":"Stochastic Optimization for Large-scale Optimal Transport","created":"2016-05-27","cited_by_count":189},{"id":"1712.00479","title":"Image to Image Translation for Domain Adaptation","created":"2017-12-01","cited_by_count":171},{"id":"1509.09259","title":"Distributionally Robust Logistic Regression","created":"2015-09-30","cited_by_count":126},{"id":"1711.02283","title":"Large-Scale Optimal Transport and Mapping Estimation","created":"2017-11-07","cited_by_count":123},{"id":"1802.04367","title":"Computational Optimal Transport: Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn's Algorithm","created":"2018-02-12","cited_by_count":112},{"id":"1306.2119","title":"Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)","created":"2013-06-10","cited_by_count":111},{"id":"1710.06276","title":"Smooth and Sparse Optimal Transport","created":"2017-10-17","cited_by_count":83},{"id":"1710.10016","title":"Regularization via Mass Transportation","created":"2017-10-27","cited_by_count":81},{"id":"1901.06482","title":"On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms","created":"2019-01-19","cited_by_count":62},{"id":"1910.13857","title":"UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization","created":"2019-10-30","cited_by_count":56},{"id":"1307.5551","title":"Regularized Discrete Optimal Transport","created":"2013-07-21","cited_by_count":54},{"id":"1706.03883","title":"Multilevel Clustering via Wasserstein Means","created":"2017-06-13","cited_by_count":49},{"id":"2007.09530","title":"A Distributionally Robust Approach to Fair Classification","created":"2020-07-18","cited_by_count":43},{"id":"1706.05218","title":"Optimal Transport for Diffeomorphic Registration","created":"2017-06-16","cited_by_count":39},{"id":"1703.04599","title":"Generalized Self-Concordant Functions: A Recipe for Newton-Type Methods","created":"2017-03-14","cited_by_count":33},{"id":"1303.6149","title":"Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression","created":"2013-03-25","cited_by_count":32},{"id":"1902.01903","title":"Exponentiated Gradient Meets Gradient Descent","created":"2019-02-05","cited_by_count":32},{"id":"1405.3843","title":"Logistic Regression: Tight Bounds for Stochastic and Online Optimization","created":"2014-05-15","cited_by_count":31},{"id":"1712.06199","title":"Structured Optimal Transport","created":"2017-12-17","cited_by_count":31},{"id":"1608.08063","title":"Wasserstein Discriminant Analysis","created":"2016-08-29","cited_by_count":25},{"id":"2012.04800","title":"A Statistical Test for Probabilistic Fairness","created":"2020-12-09","cited_by_count":25},{"id":"1610.06447","title":"Regularized Optimal Transport and the Rot Mover's Distance","created":"2016-10-20","cited_by_count":24},{"id":"1806.01879","title":"An explicit analysis of the entropic penalty in linear programming","created":"2018-06-05","cited_by_count":24},{"id":"1805.12591","title":"On Acceleration with Noise-Corrupted Gradients","created":"2018-05-31","cited_by_count":20},{"id":"1704.08200","title":"Quadratically-Regularized Optimal Transport on Graphs","created":"2017-04-26","cited_by_count":19},{"id":"1510.05466","title":"A Sparse Multi-Scale Algorithm for Dense Optimal Transport","created":"2015-10-19","cited_by_count":18},{"id":"2002.03967","title":"Regularized Optimal Transport is Ground Cost Adversarial","created":"2020-02-10","cited_by_count":17},{"id":"1506.07944","title":"Principal Geodesic Analysis for Probability Measures under the Optimal Transport Metric","created":"2015-06-26","cited_by_count":15},{"id":"1609.04495","title":"Tsallis Regularized Optimal Transport and Ecological Inference","created":"2016-09-15","cited_by_count":15},{"id":"1801.02790","title":"Better and Simpler Error Analysis of the Sinkhorn-Knopp Algorithm for Matrix Scaling","created":"2018-01-09","cited_by_count":14},{"id":"2010.05373","title":"Distributionally Robust Local Non-parametric Conditional Estimation","created":"2020-10-12","cited_by_count":13},{"id":"1609.08669","title":"A Transportation $L^p$ Distance for Signal Analysis","created":"2016-09-27","cited_by_count":11},{"id":"1710.10898","title":"Learning to solve inverse problems using Wasserstein loss","created":"2017-10-30","cited_by_count":11},{"id":"1810.07717","title":"Towards Optimal Running Times for Optimal Transport","created":"2018-10-17","cited_by_count":11},{"id":"1711.00987","title":"Analysis of Biased Stochastic Gradient Descent Using Sequential Semidefinite Programs","created":"2017-11-03","cited_by_count":10},{"id":"1810.05957","title":"Approximating optimal transport with linear programs","created":"2018-10-14","cited_by_count":10},{"id":"1906.01333","title":"Entropic regularization of continuous optimal transport problems","created":"2019-06-04","cited_by_count":10},{"id":"1803.01347","title":"Greedy stochastic algorithms for entropy-regularized optimal transport problems","created":"2018-03-04","cited_by_count":9},{"id":"1612.02273","title":"Generalized Sinkhorn iterations for regularizing inverse problems using optimal mass transport","created":"2016-12-07","cited_by_count":7},{"id":"1612.08731","title":"Quantum Optimal Transport for Tensor Field Processing","created":"2016-12-20","cited_by_count":7},{"id":"1705.04919","title":"Discovery and visualization of structural biomarkers from MRI using transport-based morphometry","created":"2017-05-14","cited_by_count":6},{"id":"1701.04072","title":"Scenario Reduction Revisited: Fundamental Limits and Guarantees","created":"2017-01-15","cited_by_count":4},{"id":"1906.00618","title":"A Direct $\\tilde{O}(1/\\epsilon)$ Iteration Parallel Algorithm for Optimal Transport","created":"2019-06-03","cited_by_count":4},{"id":"1811.02827","title":"Wasserstein variational gradient descent: From semi-discrete optimal transport to ensemble variational inference","created":"2018-11-07","cited_by_count":3},{"id":"1610.01400","title":"Convex Histogram-Based Joint Image Segmentation with Regularized Optimal Transport Cost","created":"2016-10-05","cited_by_count":2}],"next_cursor":null}