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Robust Predictable Control
Ben Eysenbach · Russ Salakhutdinov · Sergey Levine
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Many of the challenges facing today's reinforcement learning (RL) algorithms, such as robustness, generalization, transfer, and computational efficiency are closely related to compression. Prior work has convincingly argued why minimizing information is useful in the supervised learning setting, but standard RL algorithms lack an explicit mechanism for compression. The RL setting is unique because (1) its sequential nature allows an agent to use past information to avoid looking at future observations and (2) the agent can optimize its behavior to prefer states where decision making requires few bits. We take advantage of these properties to propose a method (RPC) for learning simple policies. This method brings together ideas from information bottlenecks, model-based RL, and bits-back coding into a simple and theoretically-justified algorithm. Our method jointly optimizes a latent-space model and policy to be self-consistent, such that the policy avoids states where the model is inaccurate. We demonstrate that our method achieves much tighter compression than prior methods, achieving up to 5$\times$ higher reward than a standard information bottleneck when constrained to use just 0.3 bits per observation. We also demonstrate that our method learns policies that are more robust and generalize better to new tasks.
Author Information
Ben Eysenbach (Google AI Resident)
Russ Salakhutdinov (Carnegie Mellon University)
Sergey Levine (UC Berkeley)
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Marvin Zhang · Henrik Marklund · Nikita Dhawan · Abhishek Gupta · Sergey Levine · Chelsea Finn -
2020 : Panel Discussion & Closing »
Yejin Choi · Alexei Efros · Chelsea Finn · Kristen Grauman · Quoc V Le · Yann LeCun · Ruslan Salakhutdinov · Eric Xing -
2020 : QA: Ruslan Salakhutdinov »
Ruslan Salakhutdinov -
2020 : Invited Talk: Ruslan Salakhutdinov »
Ruslan Salakhutdinov -
2020 Poster: Weakly-Supervised Reinforcement Learning for Controllable Behavior »
Lisa Lee · Benjamin Eysenbach · Russ Salakhutdinov · Shixiang (Shane) Gu · Chelsea Finn -
2020 Poster: Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement »
Benjamin Eysenbach · XINYANG GENG · Sergey Levine · Russ Salakhutdinov -
2020 Poster: A Closer Look at Accuracy vs. Robustness »
Yao-Yuan Yang · Cyrus Rashtchian · Hongyang Zhang · Russ Salakhutdinov · Kamalika Chaudhuri -
2020 Poster: Planning with General Objective Functions: Going Beyond Total Rewards »
Ruosong Wang · Peilin Zhong · Simon Du · Russ Salakhutdinov · Lin Yang -
2020 Oral: Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement »
Benjamin Eysenbach · XINYANG GENG · Sergey Levine · Russ Salakhutdinov -
2020 Poster: On Reward-Free Reinforcement Learning with Linear Function Approximation »
Ruosong Wang · Simon Du · Lin Yang · Russ Salakhutdinov -
2020 Poster: Object Goal Navigation using Goal-Oriented Semantic Exploration »
Devendra Singh Chaplot · Dhiraj Prakashchand Gandhi · Abhinav Gupta · Russ Salakhutdinov -
2020 Poster: Neural Methods for Point-wise Dependency Estimation »
Yao-Hung Hubert Tsai · Han Zhao · Makoto Yamada · Louis-Philippe Morency · Russ Salakhutdinov -
2020 Poster: Reinforcement Learning with General Value Function Approximation: Provably Efficient Approach via Bounded Eluder Dimension »
Ruosong Wang · Russ Salakhutdinov · Lin Yang -
2020 Spotlight: Neural Methods for Point-wise Dependency Estimation »
Yao-Hung Hubert Tsai · Han Zhao · Makoto Yamada · Louis-Philippe Morency · Russ Salakhutdinov -
2019 : Contributed Session - Spotlight Talks »
Jonathan Frankle · David Schwab · Ari Morcos · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · YiDing Jiang · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Sho Yaida · Muqiao Yang -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 : Lunch Break and Posters »
Xingyou Song · Elad Hoffer · Wei-Cheng Chang · Jeremy Cohen · Jyoti Islam · Yaniv Blumenfeld · Andreas Madsen · Jonathan Frankle · Sebastian Goldt · Satrajit Chatterjee · Abhishek Panigrahi · Alex Renda · Brian Bartoldson · Israel Birhane · Aristide Baratin · Niladri Chatterji · Roman Novak · Jessica Forde · YiDing Jiang · Yilun Du · Linara Adilova · Michael Kamp · Berry Weinstein · Itay Hubara · Tal Ben-Nun · Torsten Hoefler · Daniel Soudry · Hsiang-Fu Yu · Kai Zhong · Yiming Yang · Inderjit Dhillon · Jaime Carbonell · Yanqing Zhang · Dar Gilboa · Johannes Brandstetter · Alexander R Johansen · Gintare Karolina Dziugaite · Raghav Somani · Ari Morcos · Freddie Kalaitzis · Hanie Sedghi · Lechao Xiao · John Zech · Muqiao Yang · Simran Kaur · Qianli Ma · Yao-Hung Hubert Tsai · Ruslan Salakhutdinov · Sho Yaida · Zachary Lipton · Daniel Roy · Michael Carbin · Florent Krzakala · Lenka Zdeborová · Guy Gur-Ari · Ethan Dyer · Dilip Krishnan · Hossein Mobahi · Samy Bengio · Behnam Neyshabur · Praneeth Netrapalli · Kris Sankaran · Julien Cornebise · Yoshua Bengio · Vincent Michalski · Samira Ebrahimi Kahou · Md Rifat Arefin · Jiri Hron · Jaehoon Lee · Jascha Sohl-Dickstein · Samuel Schoenholz · David Schwab · Dongyu Li · Sang Choe · Henning Petzka · Ashish Verma · Zhichao Lin · Cristian Sminchisescu -
2019 : Opening Remarks »
Manzil Zaheer · Nicholas Monath · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov · Andrew McCallum -
2019 Workshop: Sets and Partitions »
Nicholas Monath · Manzil Zaheer · Andrew McCallum · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov -
2019 Workshop: Learning with Rich Experience: Integration of Learning Paradigms »
Zhiting Hu · Andrew Wilson · Chelsea Finn · Lisa Lee · Taylor Berg-Kirkpatrick · Ruslan Salakhutdinov · Eric Xing -
2019 Poster: XLNet: Generalized Autoregressive Pretraining for Language Understanding »
Zhilin Yang · Zihang Dai · Yiming Yang · Jaime Carbonell · Russ Salakhutdinov · Quoc V Le -
2019 Oral: XLNet: Generalized Autoregressive Pretraining for Language Understanding »
Zhilin Yang · Zihang Dai · Yiming Yang · Jaime Carbonell · Russ Salakhutdinov · Quoc V Le -
2019 Poster: Learning Neural Networks with Adaptive Regularization »
Han Zhao · Yao-Hung Hubert Tsai · Russ Salakhutdinov · Geoffrey Gordon -
2019 Poster: Search on the Replay Buffer: Bridging Planning and Reinforcement Learning »
Benjamin Eysenbach · Russ Salakhutdinov · Sergey Levine -
2019 Poster: Learning Data Manipulation for Augmentation and Weighting »
Zhiting Hu · Bowen Tan · Russ Salakhutdinov · Tom Mitchell · Eric Xing -
2019 Poster: Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels »
Simon Du · Kangcheng Hou · Russ Salakhutdinov · Barnabas Poczos · Ruosong Wang · Keyulu Xu -
2019 Poster: Mixtape: Breaking the Softmax Bottleneck Efficiently »
Zhilin Yang · Thang Luong · Russ Salakhutdinov · Quoc V Le -
2019 Poster: Deep Gamblers: Learning to Abstain with Portfolio Theory »
Liu Ziyin · Zhikang Wang · Paul Pu Liang · Russ Salakhutdinov · Louis-Philippe Morency · Masahito Ueda -
2019 Poster: Multiple Futures Prediction »
Yichuan Charlie Tang · Russ Salakhutdinov -
2019 Poster: On Exact Computation with an Infinitely Wide Neural Net »
Sanjeev Arora · Simon Du · Wei Hu · Zhiyuan Li · Russ Salakhutdinov · Ruosong Wang -
2019 Spotlight: On Exact Computation with an Infinitely Wide Neural Net »
Sanjeev Arora · Simon Du · Wei Hu · Zhiyuan Li · Russ Salakhutdinov · Ruosong Wang -
2018 Poster: How Many Samples are Needed to Estimate a Convolutional Neural Network? »
Simon Du · Yining Wang · Xiyu Zhai · Sivaraman Balakrishnan · Russ Salakhutdinov · Aarti Singh -
2018 Poster: Deep Generative Models with Learnable Knowledge Constraints »
Zhiting Hu · Zichao Yang · Russ Salakhutdinov · LIANHUI Qin · Xiaodan Liang · Haoye Dong · Eric Xing -
2018 Poster: GLoMo: Unsupervised Learning of Transferable Relational Graphs »
Zhilin Yang · Jake Zhao · Bhuwan Dhingra · Kaiming He · William Cohen · Russ Salakhutdinov · Yann LeCun -
2017 : Deep Kernel Learning »
Ruslan Salakhutdinov -
2017 Workshop: Deep Learning: Bridging Theory and Practice »
Sanjeev Arora · Maithra Raghu · Russ Salakhutdinov · Ludwig Schmidt · Oriol Vinyals -
2017 Oral: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Good Semi-supervised Learning That Requires a Bad GAN »
Zihang Dai · Zhilin Yang · Fan Yang · William Cohen · Ruslan Salakhutdinov -
2016 : Panel Discussion »
Gisbert Schneider · Ross E Goodwin · Simon Colton · Russ Salakhutdinov · Thorsten Joachims · Florian Pinel -
2016 : Multiplicative and Fine-grained Gating for Reading Comprehension »
Russ Salakhutdinov -
2016 Poster: Architectural Complexity Measures of Recurrent Neural Networks »
Saizheng Zhang · Yuhuai Wu · Tong Che · Zhouhan Lin · Roland Memisevic · Russ Salakhutdinov · Yoshua Bengio -
2016 Poster: Iterative Refinement of the Approximate Posterior for Directed Belief Networks »
R Devon Hjelm · Russ Salakhutdinov · Kyunghyun Cho · Nebojsa Jojic · Vince Calhoun · Junyoung Chung -
2016 Poster: Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations »
Behnam Neyshabur · Yuhuai Wu · Russ Salakhutdinov · Nati Srebro -
2016 Poster: On Multiplicative Integration with Recurrent Neural Networks »
Yuhuai Wu · Saizheng Zhang · Ying Zhang · Yoshua Bengio · Russ Salakhutdinov -
2016 Poster: Review Networks for Caption Generation »
Zhilin Yang · Ye Yuan · Yuexin Wu · William Cohen · Russ Salakhutdinov -
2016 Poster: Stochastic Variational Deep Kernel Learning »
Andrew Wilson · Zhiting Hu · Russ Salakhutdinov · Eric Xing -
2015 : Importance Weighted Autoencoders »
Russ Salakhutdinov -
2015 : Generating Images from Captions with Attention »
Russ Salakhutdinov -
2015 Poster: Skip-Thought Vectors »
Jamie Kiros · Yukun Zhu · Russ Salakhutdinov · Richard Zemel · Raquel Urtasun · Antonio Torralba · Sanja Fidler -
2015 Poster: Learning Wake-Sleep Recurrent Attention Models »
Jimmy Ba · Russ Salakhutdinov · Roger Grosse · Brendan J Frey -
2015 Spotlight: Learning Wake-Sleep Recurrent Attention Models »
Jimmy Ba · Russ Salakhutdinov · Roger Grosse · Brendan J Frey -
2015 Poster: Path-SGD: Path-Normalized Optimization in Deep Neural Networks »
Behnam Neyshabur · Russ Salakhutdinov · Nati Srebro -
2014 Poster: Learning Generative Models with Visual Attention »
Yichuan Charlie Tang · Nitish Srivastava · Russ Salakhutdinov -
2014 Poster: A Multiplicative Model for Learning Distributed Text-Based Attribute Representations »
Jamie Kiros · Richard Zemel · Russ Salakhutdinov -
2014 Demonstration: Toronto Deep Learning »
Jamie Kiros · Russ Salakhutdinov · Nitish Srivastava · Yichuan Charlie Tang -
2014 Oral: Learning Generative Models with Visual Attention »
Yichuan Charlie Tang · Nitish Srivastava · Russ Salakhutdinov -
2013 Workshop: Deep Learning »
Yoshua Bengio · Hugo Larochelle · Russ Salakhutdinov · Tomas Mikolov · Matthew D Zeiler · David Mcallester · Nando de Freitas · Josh Tenenbaum · Jian Zhou · Volodymyr Mnih -
2013 Poster: One-shot learning by inverting a compositional causal process »
Brenden M Lake · Russ Salakhutdinov · Josh Tenenbaum -
2013 Poster: Learning Stochastic Feedforward Neural Networks »
Yichuan Charlie Tang · Russ Salakhutdinov -
2013 Poster: Discriminative Transfer Learning with Tree-based Priors »
Nitish Srivastava · Russ Salakhutdinov -
2013 Poster: Annealing between distributions by averaging moments »
Roger Grosse · Chris Maddison · Russ Salakhutdinov -
2013 Oral: Annealing between distributions by averaging moments »
Roger Grosse · Chris Maddison · Russ Salakhutdinov -
2013 Poster: The Power of Asymmetry in Binary Hashing »
Behnam Neyshabur · Nati Srebro · Russ Salakhutdinov · Yury Makarychev · Payman Yadollahpour -
2012 Poster: Hamming Distance Metric Learning »
Mohammad Norouzi · Russ Salakhutdinov · David Fleet -
2012 Poster: Matrix reconstruction with the local max norm »
Rina Foygel · Nati Srebro · Russ Salakhutdinov -
2012 Poster: Multimodal Learning with Deep Boltzmann Machines »
Nitish Srivastava · Russ Salakhutdinov -
2012 Poster: A Better Way to Pre-Train Deep Boltzmann Machines »
Russ Salakhutdinov · Geoffrey E Hinton -
2012 Oral: Multimodal Learning with Deep Boltzmann Machines »
Nitish Srivastava · Russ Salakhutdinov -
2012 Poster: Cardinality Restricted Boltzmann Machines »
Kevin Swersky · Danny Tarlow · Ilya Sutskever · Richard Zemel · Russ Salakhutdinov · Ryan Adams -
2011 Workshop: Challenges in Learning Hierarchical Models: Transfer Learning and Optimization »
Quoc V. Le · Marc'Aurelio Ranzato · Russ Salakhutdinov · Josh Tenenbaum · Andrew Y Ng -
2011 Poster: Learning to Learn with Compound HD Models »
Russ Salakhutdinov · Josh Tenenbaum · Antonio Torralba -
2011 Spotlight: Learning to Learn with Compound HD Models »
Russ Salakhutdinov · Josh Tenenbaum · Antonio Torralba -
2011 Poster: Learning with the weighted trace-norm under arbitrary sampling distributions »
Rina Foygel · Russ Salakhutdinov · Ohad Shamir · Nati Srebro -
2011 Poster: Transfer Learning by Borrowing Examples »
Joseph Lim · Russ Salakhutdinov · Antonio Torralba -
2010 Workshop: Transfer Learning Via Rich Generative Models. »
Russ Salakhutdinov · Ryan Adams · Josh Tenenbaum · Zoubin Ghahramani · Tom Griffiths -
2010 Poster: Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm »
Russ Salakhutdinov · Nati Srebro -
2010 Poster: Practical Large-Scale Optimization for Max-norm Regularization »
Jason D Lee · Benjamin Recht · Russ Salakhutdinov · Nati Srebro · Joel A Tropp -
2009 Workshop: Approximate Learning of Large Scale Graphical Models »
Russ Salakhutdinov · Amir Globerson · David Sontag -
2009 Poster: Replicated Softmax: an Undirected Topic Model »
Russ Salakhutdinov · Geoffrey E Hinton -
2009 Poster: Learning in Markov Random Fields using Tempered Transitions »
Russ Salakhutdinov -
2009 Poster: Modelling Relational Data using Bayesian Clustered Tensor Factorization »
Ilya Sutskever · Russ Salakhutdinov · Josh Tenenbaum -
2008 Poster: Evaluating probabilities under high-dimensional latent variable models »
Iain Murray · Russ Salakhutdinov -
2008 Spotlight: Evaluating probabilities under high-dimensional latent variable models »
Iain Murray · Russ Salakhutdinov -
2007 Poster: Probabilistic Matrix Factorization »
Russ Salakhutdinov · Andriy Mnih -
2007 Oral: Probabilistic Matrix Factorization »
Russ Salakhutdinov · Andriy Mnih -
2007 Poster: Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes »
Russ Salakhutdinov · Geoffrey E Hinton