Learning to Optimize via Information-Directed Sampling

21 March 2014

Papers citing "Learning to Optimize via Information-Directed Sampling"

50 / 60 papers shown

Title
Toward Efficient Exploration by Large Language Model Agents Dilip Arumugam Thomas L. Griffiths LLMAG 94 1 0 29 Apr 2025
An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces Amaury Gouverneur Borja Rodríguez Gálvez T. Oechtering Mikael Skoglund 56 0 0 04 Feb 2025
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Jasmine Bayrooti Carl Henrik Ek Amanda Prorok 42 0 0 07 Oct 2024
Value of Information and Reward Specification in Active Inference and POMDPs Ran Wei 57 3 0 13 Aug 2024
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits Junghyun Lee Se-Young Yun Kwang-Sung Jun 33 4 0 19 Jul 2024
On Bits and Bandits: Quantifying the Regret-Information Trade-off Itai Shufaro Nadav Merlis Nir Weinberger Shie Mannor 38 0 0 26 May 2024
Causally Abstracted Multi-armed Bandits Fabio Massimo Zennaro Nicholas Bishop Joel Dyer Yorgos Felekis Anisoara Calinescu Michael Wooldridge Theodoros Damoulas 38 2 0 26 Apr 2024
TS-RSR: A provably efficient approach for batch bayesian optimization Zhaolin Ren Na Li 31 2 0 07 Mar 2024
Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent Yingru Li Jiawei Xu Lei Han Zhi-Quan Luo BDL OffRL 26 5 0 05 Feb 2024
An Information Theoretic Approach to Interaction-Grounded Learning Xiaoyan Hu Farzan Farnia Ho-fung Leung VLM 35 2 0 10 Jan 2024
Best Arm Identification in Batched Multi-armed Bandit Problems Sheng Cao Simai He Ruoqing Jiang Jin Xu Hongsong Yuan 12 1 0 21 Dec 2023
High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits David Young D. Leith 11 0 0 12 May 2023
Bayesian Reinforcement Learning with Limited Cognitive Load Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy OffRL 34 8 0 05 May 2023
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling Susobhan Ghosh Raphael Kim Prasidh Chhabria Raaz Dwivedi Predrag Klasjna Peng Liao Kelly Zhang Susan Murphy OffRL 22 8 0 11 Apr 2023
Thompson Sampling for Linear Bandit Problems with Normal-Gamma Priors Björn Lindenberg Karl-Olof Lindahl 25 0 0 06 Mar 2023
STEERING: Stein Information Directed Exploration for Model-Based Reinforcement Learning Souradip Chakraborty Amrit Singh Bedi Alec Koppel Mengdi Wang Furong Huang Dinesh Manocha 24 7 0 28 Jan 2023
Tight Guarantees for Interactive Decision Making with the Decision-Estimation Coefficient Dylan J. Foster Noah Golowich Yanjun Han OffRL 28 29 0 19 Jan 2023
Bayesian Fixed-Budget Best-Arm Identification Alexia Atsidakou S. Katariya Sujay Sanghavi B. Kveton 33 11 0 15 Nov 2022
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam Mark K. Ho Noah D. Goodman Benjamin Van Roy 31 4 0 30 Oct 2022
Environment Design for Inverse Reinforcement Learning Thomas Kleine Buening Victor Villin Christos Dimitrakakis 32 1 0 26 Oct 2022
Exploration via Planning for Information about the Optimal Trajectory Viraj Mehta I. Char J. Abbate R. Conlin M. Boyer Stefano Ermon J. Schneider Willie Neiswanger OffRL 27 6 0 06 Oct 2022
Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits Siddhartha Banerjee Sean R. Sinclair Milind Tambe Lily Xu Chao Yu AI4TS 31 6 0 30 Sep 2022
Risk-aware linear bandits with convex loss Patrick Saux Odalric-Ambrym Maillard 24 2 0 15 Sep 2022
Learning to Sell a Focal-ancillary Combination Hanrui Wang Xiaocheng Li Kalyan Talluri 19 0 0 23 Jul 2022
Joint Entropy Search for Maximally-Informed Bayesian Optimization Carl Hvarfner Frank Hutter Luigi Nardi 44 36 0 09 Jun 2022
Adaptive Sampling for Discovery Ziping Xu Eunjae Shim Ambuj Tewari Paul M. Zimmerman OffRL 19 4 0 30 May 2022
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits Gergely Neu Julia Olkhovskaya Matteo Papini Ludovic Schwartz 33 16 0 27 May 2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses D. Tiapkin Denis Belomestny Eric Moulines A. Naumov S. Samsonov Yunhao Tang Michal Valko Pierre Menard 31 17 0 16 May 2022
Non-Stationary Bandit Learning via Predictive Sampling Yueyang Liu Kuang Xu Benjamin Van Roy 24 19 0 04 May 2022
Truncated LinUCB for Stochastic Linear Bandits Yanglei Song Meng zhou 52 0 0 23 Feb 2022
Minimax Regret for Partial Monitoring: Infinite Outcomes and Rustichini's Regret Tor Lattimore 16 16 0 22 Feb 2022
Adaptive Experimentation in the Presence of Exogenous Nonstationary Variation Chao Qin Daniel Russo 58 6 0 18 Feb 2022
A PDE-Based Analysis of the Symmetric Two-Armed Bernoulli Bandit Vladimir A. Kobzar R. Kohn 23 4 0 11 Feb 2022
Gaussian Imagination in Bandit Learning Yueyang Liu Adithya M. Devraj Benjamin Van Roy Kuang Xu 34 7 0 06 Jan 2022
The Value of Information When Deciding What to Learn Dilip Arumugam Benjamin Van Roy 37 12 0 26 Oct 2021
Apple Tasting Revisited: Bayesian Approaches to Partially Monitored Online Binary Classification James A. Grant David S. Leslie 44 3 0 29 Sep 2021
Deep Exploration for Recommendation Systems Zheqing Zhu Benjamin Van Roy 32 11 0 26 Sep 2021
Metalearning Linear Bandits by Prior Update Amit Peleg Naama Pearl Ron Meir 37 18 0 12 Jul 2021
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control Amrit Singh Bedi Anjaly Parayil Junyu Zhang Mengdi Wang Alec Koppel 38 15 0 15 Jun 2021
Information Directed Sampling for Sparse Linear Bandits Botao Hao Tor Lattimore Wei Deng 25 19 0 29 May 2021
An Information-Theoretic Perspective on Credit Assignment in Reinforcement Learning Dilip Arumugam Peter Henderson Pierre-Luc Bacon 24 17 0 10 Mar 2021
Reinforcement Learning, Bit by Bit Xiuyuan Lu Benjamin Van Roy Vikranth Dwaracherla M. Ibrahimi Ian Osband Zheng Wen 30 70 0 06 Mar 2021
An empirical evaluation of active inference in multi-armed bandits D. Marković Hrvoje Stojić Sarah Schwöbel S. Kiebel 42 34 0 21 Jan 2021
Is Pessimism Provably Efficient for Offline RL? Ying Jin Zhuoran Yang Zhaoran Wang OffRL 27 349 0 30 Dec 2020
Randomized Value Functions via Posterior State-Abstraction Sampling Dilip Arumugam Benjamin Van Roy OffRL 31 7 0 05 Oct 2020
TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation Jackie Baek Vivek F. Farias 38 9 0 11 Jun 2020
An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson Sampling Qin Ding Cho-Jui Hsieh James Sharpnack 25 37 0 07 Jun 2020
Information Directed Sampling for Linear Partial Monitoring Johannes Kirschner Tor Lattimore Andreas Krause 24 46 0 25 Feb 2020
Making Sense of Reinforcement Learning and Probabilistic Inference Brendan O'Donoghue Ian Osband Catalin Ionescu OffRL 27 48 0 03 Jan 2020
Connections Between Mirror Descent, Thompson Sampling and the Information Ratio Julian Zimmert Tor Lattimore 22 34 0 28 May 2019