Timezone: »
Exploration policies in Bayesian bandits maximize the average reward over problem instances drawn from some distribution P. In this work, we learn such policies for an unknown distribution P using samples from P. Our approach is a form of meta-learning and exploits properties of P without making strong assumptions about its form. To do this, we parameterize our policies in a differentiable way and optimize them by policy gradients, an approach that is pleasantly general and easy to implement. We derive effective gradient estimators and propose novel variance reduction techniques. We also analyze and experiment with various bandit policy classes, including neural networks and a novel softmax policy. The latter has regret guarantees and is a natural starting point for our optimization. Our experiments show the versatility of our approach. We also observe that neural network policies can learn implicit biases expressed only through the sampled instances.
Author Information
Craig Boutilier (Google)
Chih-wei Hsu ( Google Research)
Branislav Kveton (Google Research)
Martin Mladenov (Google)
Csaba Szepesvari (DeepMind / University of Alberta)
Manzil Zaheer (Google)
More from the Same Authors
-
2021 Spotlight: On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method »
Junyu Zhang · Chengzhuo Ni · zheng Yu · Csaba Szepesvari · Mengdi Wang -
2022 : Differentially Private Adaptive Optimization with Delayed Preconditioners »
Tian Li · Manzil Zaheer · Ken Liu · Sashank Reddi · H. Brendan McMahan · Virginia Smith -
2022 : Differentially Private Adaptive Optimization with Delayed Preconditioners »
Tian Li · Manzil Zaheer · Ken Liu · Sashank Reddi · H. Brendan McMahan · Virginia Smith -
2022 : A Mixture-of-Expert Approach to RL-based Dialogue Management »
Yinlam Chow · Azamat Tulepbergenov · Ofir Nachum · Dhawal Gupta · Moonkyung Ryu · Mohammad Ghavamzadeh · Craig Boutilier -
2023 Poster: Optimistic Natural Policy Gradient: a Simple Efficient Policy Optimization Framework for Online RL »
Qinghua Liu · Gellért Weisz · András György · Chi Jin · Csaba Szepesvari -
2023 Poster: Ordering-based Conditions for Global Convergence of Policy Gradient Methods »
Jincheng Mei · Bo Dai · Alekh Agarwal · Mohammad Ghavamzadeh · Csaba Szepesvari · Dale Schuurmans -
2023 Poster: Regret Minimization via Saddle Point Optimization »
Johannes Kirschner · Alireza Bakhtiari · Kushagra Chandak · Volodymyr Tkachuk · Csaba Szepesvari -
2023 Poster: Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management »
Dhawal Gupta · Yinlam Chow · Azamat Tulepbergenov · Mohammad Ghavamzadeh · Craig Boutilier -
2023 Poster: Online RL in Linearly $q^\pi$-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore »
Gellért Weisz · András György · Csaba Szepesvari -
2023 Poster: ResMem: Learn what you can and memorize the rest »
Zitong Yang · MICHAL LUKASIK · Vaishnavh Nagarajan · Zonglin Li · Ankit Rawat · Manzil Zaheer · Aditya Menon · Sanjiv Kumar -
2023 Poster: Context-lumpable stochastic bandits »
Chung-Wei Lee · Qinghua Liu · Yasin Abbasi Yadkori · Chi Jin · Tor Lattimore · Csaba Szepesvari -
2023 Poster: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models »
Ying Fan · Olivia Watkins · Yuqing Du · Hao Liu · Moonkyung Ryu · Craig Boutilier · Pieter Abbeel · Mohammad Ghavamzadeh · Kangwook Lee · Kimin Lee -
2023 Oral: Ordering-based Conditions for Global Convergence of Policy Gradient Methods »
Jincheng Mei · Bo Dai · Alekh Agarwal · Mohammad Ghavamzadeh · Csaba Szepesvari · Dale Schuurmans -
2023 Oral: Online RL in Linearly $q^\pi$-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore »
Gellért Weisz · András György · Csaba Szepesvari -
2022 Poster: The Role of Baselines in Policy Gradient Optimization »
Jincheng Mei · Wesley Chung · Valentin Thomas · Bo Dai · Csaba Szepesvari · Dale Schuurmans -
2022 Poster: Sample-Efficient Reinforcement Learning of Partially Observable Markov Games »
Qinghua Liu · Csaba Szepesvari · Chi Jin -
2022 Poster: A Fourier Approach to Mixture Learning »
Mingda Qiao · Guru Guruganesh · Ankit Rawat · Kumar Avinava Dubey · Manzil Zaheer -
2022 Poster: Learning to Navigate Wikipedia by Taking Random Walks »
Manzil Zaheer · Kenneth Marino · Will Grathwohl · John Schultz · Wendy Shang · Sheila Babayan · Arun Ahuja · Ishita Dasgupta · Christine Kaeser-Chen · Rob Fergus -
2022 Poster: Confident Approximate Policy Iteration for Efficient Local Planning in $q^\pi$-realizable MDPs »
Gellért Weisz · András György · Tadashi Kozuno · Csaba Szepesvari -
2022 Poster: Near-Optimal Sample Complexity Bounds for Constrained MDPs »
Sharan Vaswani · Lin Yang · Csaba Szepesvari -
2022 Poster: Bandit Theory and Thompson Sampling-Guided Directed Evolution for Sequence Optimization »
Hui Yuan · Chengzhuo Ni · Huazheng Wang · Xuezhou Zhang · Le Cong · Csaba Szepesvari · Mengdi Wang -
2021 Poster: No Regrets for Learning the Prior in Bandits »
Soumya Basu · Branislav Kveton · Manzil Zaheer · Csaba Szepesvari -
2021 Poster: On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method »
Junyu Zhang · Chengzhuo Ni · zheng Yu · Csaba Szepesvari · Mengdi Wang -
2021 Poster: Understanding the Effect of Stochasticity in Policy Optimization »
Jincheng Mei · Bo Dai · Chenjun Xiao · Csaba Szepesvari · Dale Schuurmans -
2021 Poster: On the Role of Optimization in Double Descent: A Least Squares Study »
Ilja Kuzborskij · Csaba Szepesvari · Omar Rivasplata · Amal Rannen-Triki · Razvan Pascanu -
2020 Poster: Model Selection in Contextual Stochastic Bandit Problems »
Aldo Pacchiano · My Phan · Yasin Abbasi Yadkori · Anup Rao · Julian Zimmert · Tor Lattimore · Csaba Szepesvari -
2020 Poster: PLLay: Efficient Topological Layer based on Persistent Landscapes »
Kwangho Kim · Jisu Kim · Manzil Zaheer · Joon Kim · Frederic Chazal · Larry Wasserman -
2020 Poster: ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool »
Gellert Weisz · András György · Wei-I Lin · Devon Graham · Kevin Leyton-Brown · Csaba Szepesvari · Brendan Lucier -
2020 Poster: Latent Bandits Revisited »
Joey Hong · Branislav Kveton · Manzil Zaheer · Yinlam Chow · Amr Ahmed · Craig Boutilier -
2020 Poster: PAC-Bayes Analysis Beyond the Usual Bounds »
Omar Rivasplata · Ilja Kuzborskij · Csaba Szepesvari · John Shawe-Taylor -
2020 Poster: Robust large-margin learning in hyperbolic space »
Melanie Weber · Manzil Zaheer · Ankit Singh Rawat · Aditya Menon · Sanjiv Kumar -
2020 Poster: Variational Policy Gradient Method for Reinforcement Learning with General Utilities »
Junyu Zhang · Alec Koppel · Amrit Singh Bedi · Csaba Szepesvari · Mengdi Wang -
2020 Poster: Escaping the Gravitational Pull of Softmax »
Jincheng Mei · Chenjun Xiao · Bo Dai · Lihong Li · Csaba Szepesvari · Dale Schuurmans -
2020 Poster: Online Algorithm for Unsupervised Sequential Selection with Contextual Information »
Arun Verma · Manjesh Kumar Hanawal · Csaba Szepesvari · Venkatesh Saligrama -
2020 Poster: Efficient Planning in Large MDPs with Weak Linear Function Approximation »
Roshan Shariff · Csaba Szepesvari -
2020 Spotlight: Variational Policy Gradient Method for Reinforcement Learning with General Utilities »
Junyu Zhang · Alec Koppel · Amrit Singh Bedi · Csaba Szepesvari · Mengdi Wang -
2020 Oral: Escaping the Gravitational Pull of Softmax »
Jincheng Mei · Chenjun Xiao · Bo Dai · Lihong Li · Csaba Szepesvari · Dale Schuurmans -
2020 Poster: CoinDICE: Off-Policy Confidence Interval Estimation »
Bo Dai · Ofir Nachum · Yinlam Chow · Lihong Li · Csaba Szepesvari · Dale Schuurmans -
2020 Poster: Big Bird: Transformers for Longer Sequences »
Manzil Zaheer · Guru Guruganesh · Kumar Avinava Dubey · Joshua Ainslie · Chris Alberti · Santiago Ontanon · Philip Pham · Anirudh Ravula · Qifan Wang · Li Yang · Amr Ahmed -
2020 Spotlight: CoinDICE: Off-Policy Confidence Interval Estimation »
Bo Dai · Ofir Nachum · Yinlam Chow · Lihong Li · Csaba Szepesvari · Dale Schuurmans -
2019 : Coffee Break & Poster Session 1 »
Yan Zhang · Jonathon Hare · Adam Prugel-Bennett · Po Leung · Patrick Flaherty · Pitchaya Wiratchotisatian · Alessandro Epasto · Silvio Lattanzi · Sergei Vassilvitskii · Morteza Zadimoghaddam · Theja Tulabandhula · Fabian Fuchs · Adam Kosiorek · Ingmar Posner · William Hang · Anna Goldie · Sujith Ravi · Azalia Mirhoseini · Yuwen Xiong · Mengye Ren · Renjie Liao · Raquel Urtasun · Haici Zhang · Michele Borassi · Shengda Luo · Andrew Trapp · Geoffroy Dubourg-Felonneau · Yasmeen Kussad · Christopher Bender · Manzil Zaheer · Junier Oliva · Michał Stypułkowski · Maciej Zieba · Austin Dill · Chun-Liang Li · Songwei Ge · Eunsu Kang · Oiwi Parker Jones · Kelvin Ka Wing Wong · Joshua Payne · Yang Li · Azade Nazi · Erkut Erdem · Aykut Erdem · Kevin O'Connor · Juan J Garcia · Maciej Zamorski · Jan Chorowski · Deeksha Sinha · Harry Clifford · John W Cassidy -
2019 : Poster and Coffee Break 1 »
Aaron Sidford · Aditya Mahajan · Alejandro Ribeiro · Alex Lewandowski · Ali H Sayed · Ambuj Tewari · Angelika Steger · Anima Anandkumar · Asier Mujika · Hilbert J Kappen · Bolei Zhou · Byron Boots · Chelsea Finn · Chen-Yu Wei · Chi Jin · Ching-An Cheng · Christina Yu · Clement Gehring · Craig Boutilier · Dahua Lin · Daniel McNamee · Daniel Russo · David Brandfonbrener · Denny Zhou · Devesh Jha · Diego Romeres · Doina Precup · Dominik Thalmeier · Eduard Gorbunov · Elad Hazan · Elena Smirnova · Elvis Dohmatob · Emma Brunskill · Enrique Munoz de Cote · Ethan Waldie · Florian Meier · Florian Schaefer · Ge Liu · Gergely Neu · Haim Kaplan · Hao Sun · Hengshuai Yao · Jalaj Bhandari · James A Preiss · Jayakumar Subramanian · Jiajin Li · Jieping Ye · Jimmy Smith · Joan Bas Serrano · Joan Bruna · John Langford · Jonathan Lee · Jose A. Arjona-Medina · Kaiqing Zhang · Karan Singh · Yuping Luo · Zafarali Ahmed · Zaiwei Chen · Zhaoran Wang · Zhizhong Li · Zhuoran Yang · Ziping Xu · Ziyang Tang · Yi Mao · David Brandfonbrener · Shirli Di-Castro · Riashat Islam · Zuyue Fu · Abhishek Naik · Saurabh Kumar · Benjamin Petit · Angeliki Kamoutsi · Simone Totaro · Arvind Raghunathan · Rui Wu · Donghwan Lee · Dongsheng Ding · Alec Koppel · Hao Sun · Christian Tjandraatmadja · Mahdi Karami · Jincheng Mei · Chenjun Xiao · Junfeng Wen · Zichen Zhang · Ross Goroshin · Mohammad Pezeshki · Jiaqi Zhai · Philip Amortila · Shuo Huang · Mariya Vasileva · El houcine Bergou · Adel Ahmadyan · Haoran Sun · Sheng Zhang · Lukas Gruber · Yuanhao Wang · Tetiana Parshakova -
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 Poster: Think out of the "Box": Generically-Constrained Asynchronous Composite Optimization and Hedging »
Pooria Joulani · András György · Csaba Szepesvari -
2019 Poster: Detecting Overfitting via Adversarial Examples »
Roman Werpachowski · András György · Csaba Szepesvari -
2018 : Datasets and Benchmarks for Causal Learning »
Csaba Szepesvari · Isabelle Guyon · Nicolai Meinshausen · David Blei · Elias Bareinboim · Bernhard Schölkopf · Pietro Perona -
2018 : Model-free vs. Model-based Learning in a Causal World: Some Stories from Online Learning to Rank »
Csaba Szepesvari -
2018 Poster: TopRank: A practical algorithm for online stochastic ranking »
Tor Lattimore · Branislav Kveton · Shuai Li · Csaba Szepesvari -
2018 Poster: Non-delusional Q-learning and value-iteration »
Tyler Lu · Dale Schuurmans · Craig Boutilier -
2018 Poster: Nonparametric Density Estimation under Adversarial Losses »
Shashank Singh · Ananya Uppal · Boyue Li · Chun-Liang Li · Manzil Zaheer · Barnabas Poczos -
2018 Oral: Non-delusional Q-learning and value-iteration »
Tyler Lu · Dale Schuurmans · Craig Boutilier -
2018 Poster: Adaptive Methods for Nonconvex Optimization »
Manzil Zaheer · Sashank Reddi · Devendra S Sachan · Satyen Kale · Sanjiv Kumar -
2018 Poster: PAC-Bayes bounds for stable algorithms with instance-dependent priors »
Omar Rivasplata · Emilio Parrado-Hernandez · John Shawe-Taylor · Shiliang Sun · Csaba Szepesvari -
2018 Poster: Data center cooling using model-predictive control »
Nevena Lazic · Craig Boutilier · Tyler Lu · Eehern Wong · Binz Roy · Moonkyung Ryu · Greg Imwalle -
2017 Oral: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback »
Zheng Wen · Branislav Kveton · Michal Valko · Sharan Vaswani -
2017 Poster: Deep Sets »
Manzil Zaheer · Satwik Kottur · Siamak Ravanbakhsh · Barnabas Poczos · Ruslan Salakhutdinov · Alexander Smola -
2017 Poster: Multi-view Matrix Factorization for Linear Dynamical System Estimation »
Mahdi Karami · Martha White · Dale Schuurmans · Csaba Szepesvari -
2016 Poster: Following the Leader and Fast Rates in Linear Prediction: Curved Constraint Sets and Other Regularities »
Ruitong Huang · Tor Lattimore · András György · Csaba Szepesvari -
2016 Poster: SDP Relaxation with Randomized Rounding for Energy Disaggregation »
Kiarash Shaloudegi · András György · Csaba Szepesvari · Wilsun Xu -
2016 Oral: SDP Relaxation with Randomized Rounding for Energy Disaggregation »
Kiarash Shaloudegi · András György · Csaba Szepesvari · Wilsun Xu -
2015 : Confidence intervals for the mixing time of a reversible Markov chain from a single sample path »
Csaba Szepesvari -
2015 Poster: Efficient Thompson Sampling for Online Matrix-Factorization Recommendation »
Jaya Kawale · Hung H Bui · Branislav Kveton · Long Tran-Thanh · Sanjay Chawla -
2015 Poster: Online Learning with Gaussian Payoffs and Side Observations »
Yifan Wu · András György · Csaba Szepesvari -
2015 Poster: Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path »
Daniel Hsu · Aryeh Kontorovich · Csaba Szepesvari -
2015 Poster: Linear Multi-Resource Allocation with Semi-Bandit Feedback »
Tor Lattimore · Yacov Crammer · Csaba Szepesvari -
2015 Poster: Combinatorial Cascading Bandits »
Branislav Kveton · Zheng Wen · Azin Ashkan · Csaba Szepesvari -
2014 Workshop: Novel Trends and Applications in Reinforcement Learning »
Csaba Szepesvari · Marc Deisenroth · Sergey Levine · Pedro Ortega · Brian Ziebart · Emma Brunskill · Naftali Tishby · Gerhard Neumann · Daniel Lee · Sridhar Mahadevan · Pieter Abbeel · David Silver · Vicenç Gómez -
2014 Poster: Universal Option Models »
hengshuai yao · Csaba Szepesvari · Richard Sutton · Joseph Modayil · Shalabh Bhatnagar -
2013 Poster: Online Learning with Costly Features and Labels »
Navid Zolghadr · Gábor Bartók · Russell Greiner · András György · Csaba Szepesvari -
2013 Poster: Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions »
Yasin Abbasi Yadkori · Peter Bartlett · Varun Kanade · Yevgeny Seldin · Csaba Szepesvari -
2012 Session: Oral Session 6 »
Csaba Szepesvari -
2012 Poster: Deep Representations and Codes for Image Auto-Annotation »
Jamie Kiros · Csaba Szepesvari -
2011 Poster: Improved Algorithms for Linear Stochastic Bandits »
Yasin Abbasi Yadkori · David Pal · Csaba Szepesvari -
2011 Spotlight: Improved Algorithms for Linear Stochastic Bandits »
Yasin Abbasi Yadkori · David Pal · Csaba Szepesvari -
2010 Spotlight: Online Markov Decision Processes under Bandit Feedback »
Gergely Neu · András György · András Antos · Csaba Szepesvari -
2010 Poster: Online Markov Decision Processes under Bandit Feedback »
Gergely Neu · András György · Csaba Szepesvari · András Antos -
2010 Poster: Estimation of Renyi Entropy and Mutual Information Based on Generalized Nearest-Neighbor Graphs »
David Pal · Barnabas Poczos · Csaba Szepesvari -
2010 Poster: Parametric Bandits: The Generalized Linear Case »
Sarah Filippi · Olivier Cappé · Aurélien Garivier · Csaba Szepesvari -
2010 Poster: Error Propagation for Approximate Policy and Value Iteration »
Amir-massoud Farahmand · Remi Munos · Csaba Szepesvari -
2009 Poster: Multi-Step Dyna Planning for Policy Evaluation and Control »
Hengshuai Yao · Richard Sutton · Shalabh Bhatnagar · Dongcui Diao · Csaba Szepesvari -
2009 Poster: A General Projection Property for Distribution Families »
Yao-Liang Yu · Yuxi Li · Dale Schuurmans · Csaba Szepesvari -
2009 Poster: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2009 Spotlight: Convergent Temporal-Difference Learning with Arbitrary Smooth Function Approximation »
Hamid R Maei · Csaba Szepesvari · Shalabh Batnaghar · Doina Precup · David Silver · Richard Sutton -
2008 Poster: Online Optimization in X-Armed Bandits »
Sebastien Bubeck · Remi Munos · Gilles Stoltz · Csaba Szepesvari -
2008 Poster: Regularized Policy Iteration »
Amir-massoud Farahmand · Mohammad Ghavamzadeh · Csaba Szepesvari · Shie Mannor -
2008 Poster: A Convergent O(n) Temporal-difference Algorithm for Off-policy Learning with Linear Function Approxi »
Richard Sutton · Csaba Szepesvari · Hamid R Maei -
2007 Poster: Fitted Q-iteration in continuous action-space MDPs »
Remi Munos · András Antos · Csaba Szepesvari