Distances for Markov chains from sample streams

23 May 2025

Papers citing "Distances for Markov chains from sample streams"

25 / 25 papers shown

Title
Gymnasium: A Standard Interface for Reinforcement Learning Environments Mark Towers Ariel Kwiatkowski Jordan Terry John U. Balis Gianluca De Cola ... Andrea Pierré Sander Schulhoff Jun Jet Tai Hannah Tan Omar G. Younis AuLLM OffRL 40 183 0 24 Jul 2024
Bisimulation Metrics are Optimal Transport Distances, and Can be Computed Efficiently Sergio Calo Anders Jonsson Gergely Neu Ludovic Schwartz Javier Segovia OT 59 2 0 06 Jun 2024
High Rank Path Development: an approach of learning the filtration of stochastic processes Jiajie Tao Hao Ni Chong Liu 35 1 0 23 May 2024
A Note on Loss Functions and Error Compounding in Model-based Reinforcement Learning Nan Jiang 43 6 0 15 Apr 2024
Dealing with unbounded gradients in stochastic saddle-point optimization Gergely Neu Nneka Okolo 54 4 0 21 Feb 2024
Distances for Markov Chains, and Their Differentiation Tristan Brugere Zhengchao Wan Yusu Wang OT OOD 45 4 0 16 Feb 2023
Approximate Policy Iteration with Bisimulation Metrics Mete Kemertas Allan D. Jepson 40 8 0 06 Feb 2022
Minibatch optimal transport distances; analysis and applications Kilian Fatras Younes Zine Szymon Majewski Rémi Flamary Rémi Gribonval Nicolas Courty OT 83 57 0 05 Jan 2021
Learning Invariant Representations for Reinforcement Learning without Reconstruction Amy Zhang R. McAllister Roberto Calandra Y. Gal Sergey Levine OOD SSL 73 469 0 18 Jun 2020
COT-GAN: Generating Sequential Data via Causal Optimal Transport Tianlin Xu L. Wenliang Michael Munn Beatrice Acciaio GAN CML 28 96 0 15 Jun 2020
Stochastic Optimization for Regularized Wasserstein Estimators Marin Ballu Quentin Berthet Francis R. Bach 14 16 0 20 Feb 2020
Scalable methods for computing state similarity in deterministic Markov Decision Processes Pablo Samuel Castro 29 136 0 21 Nov 2019
Learning with minibatch Wasserstein : asymptotic and gradient properties Kilian Fatras Younes Zine Rémi Flamary Rémi Gribonval Nicolas Courty OT 17 91 0 09 Oct 2019
Provably efficient RL with Rich Observations via Latent State Decoding S. Du A. Krishnamurthy Nan Jiang Alekh Agarwal Miroslav Dudík John Langford OffRL 11 230 0 25 Jan 2019
Empirical Regularized Optimal Transport: Statistical Theory and Applications M. Klatt Carla Tameling Axel Munk OT 49 61 0 23 Oct 2018
Optimal Transport for structured data with application on graphs Titouan Vayer Laetitia Chapel Rémi Flamary R. Tavenard Nicolas Courty OT 39 270 0 23 May 2018
Computational Optimal Transport Gabriel Peyré Marco Cuturi OT 70 2,133 0 01 Mar 2018
Large-Scale Optimal Transport and Mapping Estimation Vivien Seguy B. Damodaran Rémi Flamary Nicolas Courty Antoine Rolet Mathieu Blondel OT 50 245 0 07 Nov 2017
Learning Generative Models with Sinkhorn Divergences Aude Genevay Gabriel Peyré Marco Cuturi OT 105 625 0 01 Jun 2017
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration Jason M. Altschuler Jonathan Niles-Weed Philippe Rigollet OT 45 586 0 26 May 2017
Stochastic Optimization for Large-scale Optimal Transport Aude Genevay Marco Cuturi Gabriel Peyré Francis R. Bach OT 41 464 0 27 May 2016
On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities Alexander Rakhlin Karthik Sridharan 24 48 0 13 Oct 2015
Continuous control with deep reinforcement learning Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel N. Heess Tom Erez Yuval Tassa David Silver Daan Wierstra 104 13,174 0 09 Sep 2015
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances Marco Cuturi OT 52 4,210 0 04 Jun 2013
Metrics for Finite Markov Decision Processes N. Ferns Prakash Panangaden Doina Precup 42 321 0 11 Jul 2012