Deep Reinforcement Learning that Matters

19 September 2017

Papers citing "Deep Reinforcement Learning that Matters"

50 / 316 papers shown

Title
Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddings Gregor Wiedemann Steffen Remus Avi Chawla Chris Biemann 21 174 0 23 Sep 2019
Leveraging Human Guidance for Deep Reinforcement Learning Tasks Ruohan Zhang F. Torabi L. Guan D. Ballard Peter Stone 11 87 0 21 Sep 2019
DECoVaC: Design of Experiments with Controlled Variability Components Thomas Boquet Laure Delisle Denis Kochetkov Nathan Schucher Parmida Atighehchian Boris N. Oreshkin Julien Cornebise 22 1 0 21 Sep 2019
Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification Jiawei Wu Wenhan Xiong William Yang Wang 18 69 0 09 Sep 2019
Is Deep Reinforcement Learning Really Superhuman on Atari? Leveling the playing field Marin Toromanoff É. Wirbel Fabien Moutarde OffRL 22 24 0 13 Aug 2019
Behaviour Suite for Reinforcement Learning Ian Osband Yotam Doron Matteo Hessel John Aslanides Eren Sezener ... Satinder Singh Benjamin Van Roy R. Sutton David Silver H. V. Hasselt OffRL 24 178 0 09 Aug 2019
Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems M. Lutter Kim D. Listmann Jan Peters PINN 16 71 0 10 Jul 2019
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates Ning Liu Xiaolong Ma Zhiyuan Xu Yanzhi Wang Jian Tang Jieping Ye 35 183 0 06 Jul 2019
Co-training for Policy Learning Jialin Song Ravi Lanka Yisong Yue M. Ono OffRL 8 19 0 03 Jul 2019
Hyp-RL : Hyperparameter Optimization by Reinforcement Learning H. Jomaa Josif Grabocka Lars Schmidt-Thieme 23 65 0 27 Jun 2019
Neural Proximal/Trust Region Policy Optimization Attains Globally Optimal Policy Boyi Liu Qi Cai Zhuoran Yang Zhaoran Wang 22 108 0 25 Jun 2019
Modern Deep Reinforcement Learning Algorithms Sergey Ivanov A. Dýakonov OffRL 21 38 0 24 Jun 2019
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration Brahma S. Pavse F. Torabi Josiah P. Hanna Garrett A. Warnell Peter Stone 19 33 0 18 Jun 2019
Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains Matthieu Zimmer Paul Weng 13 7 0 10 Jun 2019
An Empirical Study on Hyperparameters and their Interdependence for RL Generalization Xingyou Song Yilun Du Jacob Jackson AI4CE 19 8 0 02 Jun 2019
On Network Design Spaces for Visual Recognition Ilija Radosavovic Justin Johnson Saining Xie Wan-Yen Lo Piotr Dollár 17 134 0 30 May 2019
REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning Brian Yang Jesse Zhang Vitchyr H. Pong Sergey Levine Dinesh Jayaraman 14 37 0 17 May 2019
The Scientific Method in the Science of Machine Learning Jessica Zosa Forde Michela Paganini 24 35 0 24 Apr 2019
Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation Weijia Xu Xing Niu Marine Carpuat 16 10 0 04 Apr 2019
Deep Reinforcement Learning on a Budget: 3D Control and Reasoning Without a Supercomputer E. Beeching Christian Wolf J. Dibangoye Olivier Simonin OffRL LRM 32 25 0 03 Apr 2019
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies Riley Simmons-Edler Ben Eisner E. Mitchell Sebastian Seung Daniel D. Lee 21 28 0 25 Mar 2019
Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics Denis Steckelmacher Hélène Plisnier D. Roijers A. Nowé OffRL 18 17 0 11 Mar 2019
The AI Driving Olympics at NeurIPS 2018 J. Zilly J. Tani Breandan Considine Bhairav Mehta Andrea F. Daniele ... R. Hristov S. Mallya Emilio Frazzoli A. Censi Liam Paull 16 14 0 06 Mar 2019
Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learning Ruo-Ze Liu Haifeng Guo Xiaozhong Ji Yang Yu Zhen-Jia Pang Zitai Xiao Yuzhou Wu Tong Lu OffRL 19 13 0 02 Mar 2019
Neural Packet Classification Eric Liang Hang Zhu Xin Jin Ion Stoica OffRL 35 120 0 27 Feb 2019
Investigating Generalisation in Continuous Deep Reinforcement Learning Chenyang Zhao Olivier Sigaud F. Stulp Timothy M. Hospedales OffRL 14 48 0 19 Feb 2019
Fast Efficient Hyperparameter Tuning for Policy Gradients Supratik Paul Vitaly Kurin Shimon Whiteson 22 32 0 18 Feb 2019
Neural-encoding Human Experts' Domain Knowledge to Warm Start Reinforcement Learning Andrew Silva Matthew C. Gombolay OffRL 19 20 0 15 Feb 2019
Ten ways to fool the masses with machine learning F. Minhas Amina Asif Asa Ben-Hur FedML HAI 13 5 0 07 Jan 2019
Learning to Walk via Deep Reinforcement Learning Tuomas Haarnoja Sehoon Ha Aurick Zhou Jie Tan George Tucker Sergey Levine 29 433 0 26 Dec 2018
TD-Regularized Actor-Critic Methods Simone Parisi Voot Tangkaratt Jan Peters Mohammad Emtiyaz Khan OffRL 14 31 0 19 Dec 2018
Dopamine: A Research Framework for Deep Reinforcement Learning Pablo Samuel Castro Subhodeep Moitra Carles Gelada Saurabh Kumar Marc G. Bellemare OffRL 17 276 0 14 Dec 2018
Distilling Information from a Flood: A Possibility for the Use of Meta-Analysis and Systematic Review in Machine Learning Research Peter Henderson Emma Brunskill AI4CE 29 3 0 03 Dec 2018
A Closer Look at Deep Policy Gradients Andrew Ilyas Logan Engstrom Shibani Santurkar Dimitris Tsipras Firdaus Janoos Larry Rudolph Aleksander Madry 22 50 0 06 Nov 2018
Assessing Generalization in Deep Reinforcement Learning Charles Packer Katelyn Gao Jernej Kos Philipp Krahenbuhl V. Koltun D. Song OffRL 18 233 0 29 Oct 2018
RLgraph: Modular Computation Graphs for Deep Reinforcement Learning Michael Schaarschmidt Sven Mika Kai Fricke Eiko Yoneki OffRL 23 5 0 21 Oct 2018
Learning Socially Appropriate Robot Approaching Behavior Toward Groups using Deep Reinforcement Learning Yuan Gao Fangkai Yang Martin Frisk Daniel Hernández Christopher E. Peters Ginevra Castellano 24 5 0 16 Oct 2018
A Survey and Critique of Multiagent Deep Reinforcement Learning Pablo Hernandez-Leal Bilal Kartal Matthew E. Taylor OffRL 32 550 0 12 Oct 2018
PPO-CMA: Proximal Policy Optimization with Covariance Matrix Adaptation Perttu Hämäläinen Amin Babadi Xiaoxiao Ma J. Lehtinen 29 62 0 05 Oct 2018
CEM-RL: Combining evolutionary and gradient-based methods for policy search Aloïs Pourchot Olivier Sigaud 22 159 0 02 Oct 2018
SmartChoices: Hybridizing Programming and Machine Learning Victor Carbune Thierry Coppey A. Daryin Thomas Deselaers Nikhil Sarda J. Yagnik 16 2 0 01 Oct 2018
Generalization and Regularization in DQN Jesse Farebrother Marlos C. Machado Michael Bowling 25 203 0 29 Sep 2018
Deterministic Implementations for Reproducibility in Deep Reinforcement Learning P. Nagarajan Garrett A. Warnell Peter Stone 12 51 0 15 Sep 2018
Improving Optimization Bounds using Machine Learning: Decision Diagrams meet Deep Reinforcement Learning Quentin Cappart Emmanuel Goutierre David Bergman Louis-Martin Rousseau AI4CE 10 55 0 10 Sep 2018
How clever is the FiLM model, and how clever can it be? A. Kuhnle Huiyuan Xie Ann A. Copestake 22 6 0 09 Sep 2018
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning Ilya Kostrikov Kumar Krishna Agrawal Debidatta Dwibedi Sergey Levine Jonathan Tompson 32 256 0 09 Sep 2018
A Study of Reinforcement Learning for Neural Machine Translation Lijun Wu Fei Tian Tao Qin Jianhuang Lai Tie-Yan Liu OffRL 27 182 0 27 Aug 2018
Policy Optimization as Wasserstein Gradient Flows Ruiyi Zhang Changyou Chen Chunyuan Li Lawrence Carin 14 66 0 09 Aug 2018
CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving Xiaodan Liang Tairui Wang Luona Yang Eric P. Xing 19 266 0 10 Jul 2018
Troubling Trends in Machine Learning Scholarship Zachary Chase Lipton Jacob Steinhardt 21 288 0 09 Jul 2018