`

Timezone: »

 
Poster
Empirical Likelihood for Contextual Bandits
Nikos Karampatziakis · John Langford · Paul Mineiro

Thu Dec 10 09:00 AM -- 11:00 AM (PST) @ Poster Session 5 #1662

We propose an estimator and confidence interval for computing the value of a policy from off-policy data in the contextual bandit setting. To this end we apply empirical likelihood techniques to formulate our estimator and confidence interval as simple convex optimization problems. Using the lower bound of our confidence interval, we then propose an off-policy policy optimization algorithm that searches for policies with large reward lower bound. We empirically find that both our estimator and confidence interval improve over previous proposals in finite sample regimes. Finally, the policy optimization algorithm we propose outperforms a strong baseline system for learning from off-policy data.

Author Information

Nikos Karampatziakis (Microsoft)
John Langford (Microsoft Research New York)
Paul Mineiro (Microsoft)

More from the Same Authors

  • 2021 Poster: Bellman-consistent Pessimism for Offline Reinforcement Learning »
    Tengyang Xie · Ching-An Cheng · Nan Jiang · Paul Mineiro · Alekh Agarwal
  • 2021 Oral: Bellman-consistent Pessimism for Offline Reinforcement Learning »
    Tengyang Xie · Ching-An Cheng · Nan Jiang · Paul Mineiro · Alekh Agarwal
  • 2020 : Panel »
    Emma Brunskill · Nan Jiang · Nando de Freitas · Finale Doshi-Velez · Sergey Levine · John Langford · Lihong Li · George Tucker · Rishabh Agarwal · Aviral Kumar
  • 2020 : Causal Structure Discovery in RL »
    John Langford
  • 2020 Poster: Efficient Contextual Bandits with Continuous Actions »
    Maryam Majzoubi · Chicheng Zhang · Rajan Chari · Akshay Krishnamurthy · John Langford · Aleksandrs Slivkins
  • 2020 Poster: Learning the Linear Quadratic Regulator from Nonlinear Observations »
    Zakaria Mhammedi · Dylan Foster · Max Simchowitz · Dipendra Misra · Wen Sun · Akshay Krishnamurthy · Alexander Rakhlin · John Langford
  • 2020 : Real World RL with Vowpal Wabbit: Beyond Contextual Bandits »
    John Langford · Marek Wydmuch · Maryam Majzoubi · Adith Swaminathan · · Dylan Foster · Paul Mineiro
  • 2019 : Poster and Coffee Break 2 »
    Karol Hausman · Kefan Dong · Ken Goldberg · Lihong Li · Lin Yang · Lingxiao Wang · Lior Shani · Liwei Wang · Loren Amdahl-Culleton · Lucas Cassano · Marc Dymetman · Marc Bellemare · Marcin Tomczak · Margarita Castro · Marius Kloft · Marius-Constantin Dinu · Markus Holzleitner · Martha White · Mengdi Wang · Michael Jordan · Mihailo Jovanovic · Ming Yu · Minshuo Chen · Moonkyung Ryu · Muhammad Zaheer · Naman Agarwal · Nan Jiang · Niao He · Nikolaus Yasui · Nikos Karampatziakis · Nino Vieillard · Ofir Nachum · Olivier Pietquin · Ozan Sener · Pan Xu · Parameswaran Kamalaruban · Paul Mineiro · Paul Rolland · Philip Amortila · Pierre-Luc Bacon · Prakash Panangaden · Qi Cai · Qiang Liu · Quanquan Gu · Raihan Seraj · Richard Sutton · Rick Valenzano · Robert Dadashi · Rodrigo Toro Icarte · Roshan Shariff · Roy Fox · Ruosong Wang · Saeed Ghadimi · Samuel Sokota · Sean Sinclair · Sepp Hochreiter · Sergey Levine · Sergio Valcarcel Macua · Sham Kakade · Shangtong Zhang · Sheila McIlraith · Shie Mannor · Shimon Whiteson · Shuai Li · Shuang Qiu · Wai Lok Li · Siddhartha Banerjee · Sitao Luan · Tamer Basar · Thinh Doan · Tianhe Yu · Tianyi Liu · Tom Zahavy · Toryn Klassen · Tuo Zhao · Vicenç Gómez · Vincent Liu · Volkan Cevher · Wesley Suttle · Xiao-Wen Chang · Xiaohan Wei · Xiaotong Liu · Xingguo Li · Xinyi Chen · Xingyou Song · Yao Liu · YiDing Jiang · Yihao Feng · Yilun Du · Yinlam Chow · Yinyu Ye · Yishay Mansour · · Yonathan Efroni · Yongxin Chen · Yuanhao Wang · Bo Dai · Chen-Yu Wei · Harsh Shrivastava · Hongyang Zhang · Qinqing Zheng · SIDDHARTHA SATPATHI · Xueqing Liu · Andreu Vall
  • 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 (Vincent) 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 : Poster Spotlight 1 »
    David Brandfonbrener · Joan Bruna · Tom Zahavy · Haim Kaplan · Yishay Mansour · Nikos Karampatziakis · John Langford · Paul Mineiro · Donghwan Lee · Niao He
  • 2019 Poster: Efficient Forward Architecture Search »
    Hanzhang Hu · John Langford · Rich Caruana · Saurajit Mukherjee · Eric Horvitz · Debadeepta Dey
  • 2018 Poster: On Oracle-Efficient PAC RL with Rich Observations »
    Christoph Dann · Nan Jiang · Akshay Krishnamurthy · Alekh Agarwal · John Langford · Robert Schapire
  • 2018 Spotlight: On Oracle-Efficient PAC RL with Rich Observations »
    Christoph Dann · Nan Jiang · Akshay Krishnamurthy · Alekh Agarwal · John Langford · Robert Schapire
  • 2017 : Panel »
    Garth Gibson · Joseph Gonzalez · John Langford · Dawn Song
  • 2017 : John Langford (MSR) on Dreaming Contextual Memory »
    John Langford
  • 2017 Poster: Off-policy evaluation for slate recommendation »
    Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
  • 2017 Oral: Off-policy evaluation for slate recommendation »
    Adith Swaminathan · Akshay Krishnamurthy · Alekh Agarwal · Miro Dudik · John Langford · Damien Jose · Imed Zitouni
  • 2016 Workshop: Let's Discuss: Learning Methods for Dialogue »
    Hal Daumé III · Paul Mineiro · Amanda Stent · Jason E Weston
  • 2016 Poster: Efficient Second Order Online Learning by Sketching »
    Haipeng Luo · Alekh Agarwal · Nicolò Cesa-Bianchi · John Langford
  • 2016 Poster: A Credit Assignment Compiler for Joint Prediction »
    Kai-Wei Chang · He He · Stephane Ross · Hal Daumé III · John Langford
  • 2016 Poster: PAC Reinforcement Learning with Rich Observations »
    Akshay Krishnamurthy · Alekh Agarwal · John Langford
  • 2016 Poster: Search Improves Label for Active Learning »
    Alina Beygelzimer · Daniel Hsu · John Langford · Chicheng Zhang
  • 2015 Poster: Logarithmic Time Online Multiclass prediction »
    Anna Choromanska · John Langford
  • 2015 Poster: Efficient and Parsimonious Agnostic Active Learning »
    Tzu-Kuo Huang · Alekh Agarwal · Daniel Hsu · John Langford · Robert Schapire
  • 2015 Spotlight: Logarithmic Time Online Multiclass prediction »
    Anna Choromanska · John Langford
  • 2015 Spotlight: Efficient and Parsimonious Agnostic Active Learning »
    Tzu-Kuo Huang · Alekh Agarwal · Daniel Hsu · John Langford · Robert Schapire
  • 2013 Workshop: Extreme Classification: Multi-Class & Multi-Label Learning with Millions of Categories »
    Manik Varma · John Langford