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Exploration by Optimisation in Partial Monitoring

Annual Conference Computational Learning Theory (COLT), 2019

12 July 2019

Tor Lattimore

Csaba Szepesvári

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Papers citing "Exploration by Optimisation in Partial Monitoring"

22 / 22 papers shown

Title
Instance-Dependent Regret Bounds for Nonstochastic Linear Partial Monitoring Federico Di Gennaro Khaled Eldowa Nicolò Cesa-Bianchi 72 0 0 22 Oct 2025
Beyond Covariance Matrix: The Statistical Complexity of Private Linear Regression Fan Chen Jiachun Li Alexander Rakhlin D. Simchi-Levi 320 2 0 18 Feb 2025
Decision Making in Hybrid Environments: A Model Aggregation ApproachAnnual Conference Computational Learning Theory (COLT), 2025 Haolin Liu Chen-Yu Wei Julian Zimmert 391 0 0 09 Feb 2025
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit LearnabilityNeural Information Processing Systems (NeurIPS), 2024 Fan Chen Dylan J. Foster Yanjun Han Jian Qian Alexander Rakhlin Yunbei Xu 204 3 0 07 Oct 2024
$A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $Θ(T^{2/3})$ and its Application to Best-of-Both-Worlds$ A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $Θ(T^{2/3})$ and its Application to Best-of-Both-Worlds Taira Tsuchiya Shinji Ito 180 2 0 30 May 2024
Regret Minimization via Saddle Point OptimizationNeural Information Processing Systems (NeurIPS), 2024 Johannes Kirschner Seyed Alireza Bakhtiari Kushagra Chandak Volodymyr Tkachuk Csaba Szepesvári 140 2 0 15 Mar 2024
Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring Taira Tsuchiya Shinji Ito Junya Honda 196 3 0 13 Feb 2024
Randomized Confidence Bounds for Stochastic Partial Monitoring M. Heuillet Ola Ahmad Audrey Durand 272 1 0 07 Feb 2024
On the Minimax Regret in Online Ranking with Top-k Feedback Mingyuan Zhang Ambuj Tewari 148 0 0 05 Sep 2023
Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worldsNeural Information Processing Systems (NeurIPS), 2023 Taira Tsuchiya Shinji Ito Junya Honda 167 12 0 26 May 2023
Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and ApplicationsJournal of machine learning research (JMLR), 2023 Johannes Kirschner Tor Lattimore Andreas Krause 199 10 0 07 Feb 2023
Best-of-Both-Worlds Algorithms for Partial MonitoringInternational Conference on Algorithmic Learning Theory (ALT), 2022 Taira Tsuchiya Shinji Ito Junya Honda 290 18 0 29 Jul 2022
On the Complexity of Adversarial Decision MakingNeural Information Processing Systems (NeurIPS), 2022 Dylan J. Foster Alexander Rakhlin Ayush Sekhari Karthik Sridharan AAML 134 30 0 27 Jun 2022
Minimax Regret for Partial Monitoring: Infinite Outcomes and Rustichini's RegretAnnual Conference Computational Learning Theory (COLT), 2022 Tor Lattimore 121 17 0 22 Feb 2022
Gaussian Imagination in Bandit Learning Yueyang Liu Adithya M. Devraj Benjamin Van Roy Kuang Xu 172 7 0 06 Jan 2022
Isotuning With Applications To Scale-Free Online Learning Laurent Orseau Marcus Hutter 228 6 0 29 Dec 2021
Scale-Free Adversarial Multi-Armed Bandit with Arbitrary Feedback Delays Jiatai Huang Yan Dai Longbo Huang AI4CE 309 2 0 26 Oct 2021
Scale Free Adversarial Multi Armed BanditsInternational Conference on Algorithmic Learning Theory (ALT), 2021 Sudeep Raja Putta Shipra Agrawal 157 11 0 08 Jun 2021
A Bit Better? Quantifying Information for Bandit Learning Adithya M. Devraj Benjamin Van Roy Kuang Xu 100 5 0 18 Feb 2021
Mirror Descent and the Information RatioAnnual Conference Computational Learning Theory (COLT), 2020 Tor Lattimore András Gyorgy 202 44 0 25 Sep 2020
Matrix games with bandit feedback Brendan O'Donoghue Tor Lattimore Ian Osband 113 11 0 09 Jun 2020
Information Directed Sampling for Linear Partial MonitoringAnnual Conference Computational Learning Theory (COLT), 2020 Johannes Kirschner Tor Lattimore Andreas Krause 187 49 0 25 Feb 2020