Sampling Through the Lens of Sequential Decision Making

17 August 2022

Papers citing "Sampling Through the Lens of Sequential Decision Making"

46 / 46 papers shown

Title
COEM: Cross-Modal Embedding for MetaCell Identification Haiyi Mao M. Jia Jason Xiaotian Dou Haotian Zhang J. Benos 33 7 0 15 Jul 2022
CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery Michael Laskin Hao Liu Xue Bin Peng Denis Yarats Aravind Rajeswaran Pieter Abbeel SSL 126 68 0 01 Feb 2022
Decentralized Mean Field Games Sriram Ganapathi Subramanian Matthew E. Taylor Mark Crowley Pascal Poupart OOD OffRL 73 15 0 16 Dec 2021
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization Aviral Kumar Rishabh Agarwal Tengyu Ma Aaron Courville George Tucker Sergey Levine OffRL 58 69 0 09 Dec 2021
Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks Soroush Nasiriany Huihan Liu Yuke Zhu 108 112 0 07 Oct 2021
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 51 83 0 08 Sep 2021
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning Erdun Gao Fan Feng Chaochao Lu Sara Magliacane Kun Zhang 78 68 0 06 Jul 2021
Decision Transformer: Reinforcement Learning via Sequence Modeling Lili Chen Kevin Lu Aravind Rajeswaran Kimin Lee Aditya Grover Michael Laskin Pieter Abbeel A. Srinivas Igor Mordatch OffRL 114 1,638 0 02 Jun 2021
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset Chuizheng Meng Loc Trinh Nan Xu Yan Liu 49 30 0 12 Feb 2021
Partially Observable Mean Field Reinforcement Learning Sriram Ganapathi Subramanian Matthew E. Taylor Mark Crowley Pascal Poupart OOD 64 27 0 31 Dec 2020
Is Pessimism Provably Efficient for Offline RL? Ying Jin Zhuoran Yang Zhaoran Wang OffRL 159 358 0 30 Dec 2020
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning Avi Singh Huihan Liu G. Zhou Albert Yu Nicholas Rhinehart Sergey Levine OffRL OnRL 56 142 0 19 Nov 2020
Thinking Fast and Slow in AI G. Booch F. Fabiano L. Horesh Kiran Kate J. Lenchner ... Andrea Loreggia K. Murugesan Nicholas Mattei F. Rossi Biplav Srivastava 63 96 0 12 Oct 2020
Is Reinforcement Learning More Difficult Than Bandits? A Near-optimal Algorithm Escaping the Curse of Horizon Zihan Zhang Xiangyang Ji S. Du OffRL 95 105 0 28 Sep 2020
Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge Kai Sun Dian Yu Jianshu Chen Dong Yu Claire Cardie 49 12 0 12 Sep 2020
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search? Shen Yan Yu Zheng Wei Ao Xiao Zeng Mi Zhang SSL AI4CE 78 102 0 12 Jun 2020
Contrastive Multi-View Representation Learning on Graphs Kaveh Hassani Amir Hosein Khas Ahmadi SSL 222 1,301 0 10 Jun 2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior Lisa Lee Benjamin Eysenbach Ruslan Salakhutdinov S. Gu Chelsea Finn SSL 62 26 0 06 Apr 2020
Revisiting Training Strategies and Generalization Performance in Deep Metric Learning Karsten Roth Timo Milbich Samarth Sinha Prateek Gupta Bjorn Ommer Joseph Paul Cohen 49 170 0 19 Feb 2020
Multi Type Mean Field Reinforcement Learning Sriram Ganapathi Subramanian Pascal Poupart Matthew E. Taylor N. Hegde AI4CE 40 56 0 06 Feb 2020
Provably Efficient Exploration in Policy Optimization Qi Cai Zhuoran Yang Chi Jin Zhaoran Wang 51 281 0 12 Dec 2019
Convergent Policy Optimization for Safe Reinforcement Learning Ming Yu Zhuoran Yang Mladen Kolar Zhaoran Wang 63 95 0 26 Oct 2019
Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Lingxiao Wang Qi Cai Zhuoran Yang Zhaoran Wang 80 241 0 29 Aug 2019
Large Scale Adversarial Representation Learning Jeff Donahue Karen Simonyan SSL 124 543 0 04 Jul 2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model Alex X. Lee Anusha Nagabandi Pieter Abbeel Sergey Levine OffRL BDL 78 380 0 01 Jul 2019
Global Convergence of Policy Gradient Methods to (Almost) Locally Optimal Policies Kai Zhang Alec Koppel Haoqi Zhu Tamer Basar 65 190 0 19 Jun 2019
DeepMDP: Learning Continuous Latent Space Models for Representation Learning Carles Gelada Saurabh Kumar Jacob Buckman Ofir Nachum Marc G. Bellemare BDL 75 287 0 06 Jun 2019
Learning Actionable Representations with Goal-Conditioned Policies Dibya Ghosh Abhishek Gupta Sergey Levine 61 109 0 19 Nov 2018
Visual Reinforcement Learning with Imagined Goals Ashvin Nair Vitchyr H. Pong Murtaza Dalal Shikhar Bahl Steven Lin Sergey Levine SSL 75 543 0 12 Jul 2018
Unsupervised Video Object Segmentation for Deep Reinforcement Learning Vikrant Goel James Weng Pascal Poupart OCL 59 66 0 20 May 2018
Mean Field Multi-Agent Reinforcement Learning Yaodong Yang Rui Luo Minne Li M. Zhou Weinan Zhang Jun Wang AI4CE 61 574 0 15 Feb 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor Tuomas Haarnoja Aurick Zhou Pieter Abbeel Sergey Levine 292 8,329 0 04 Jan 2018
What Words Do We Use to Lie?: Word Choice in Deceptive Messages J. Dou Michelle Liu Haaris Muneer Adam Schlussel 20 6 0 01 Oct 2017
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization Aryan Mokhtari Alejandro Ribeiro 59 20 0 02 Sep 2017
Proximal Policy Optimization Algorithms John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov OffRL 473 19,006 0 20 Jul 2017
Sampling Matters in Deep Embedding Learning Chaoxia Wu R. Manmatha Alex Smola Philipp Krahenbuhl 92 923 0 23 Jun 2017
Loss is its own Reward: Self-Supervision for Reinforcement Learning Evan Shelhamer Parsa Mahmoudieh Max Argus Trevor Darrell SSL 77 186 0 21 Dec 2016
Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method Lihua Lei Michael I. Jordan 82 96 0 12 Sep 2016
Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy Aryan Mokhtari Alejandro Ribeiro ODL 44 32 0 24 May 2016
On Deep Multi-View Representation Learning: Objectives and Optimization Weiran Wang R. Arora Karen Livescu J. Bilmes SSL DRL 74 914 0 02 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,814 0 10 Dec 2015
Deep Metric Learning via Lifted Structured Feature Embedding Hyun Oh Song Yu Xiang Stefanie Jegelka Silvio Savarese FedML SSL DML 94 1,641 0 19 Nov 2015
FaceNet: A Unified Embedding for Face Recognition and Clustering Florian Schroff Dmitry Kalenichenko James Philbin 3DH 361 13,143 0 12 Mar 2015
Vector-space Analysis of Belief-state Approximation for POMDPs Pascal Poupart Craig Boutilier 68 18 0 10 Jan 2013
Anytime Marginal MAP Inference Denis Deratani Mauá Cassio Polpo de Campos 52 24 0 27 Jun 2012
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 253 12,431 0 24 Jun 2012