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Poster
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Wed 16:30
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An Equivalence Between Static and Dynamic Regret Minimization
Andrew Jacobsen · Francesco Orabona
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Poster
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Wed 16:30
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Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
Victor Boone · Zihan Zhang
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Poster
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Fri 11:00
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Federated Online Prediction from Experts with Differential Privacy: Separations and Regret Speed-ups
Fengyu Gao · Ruiquan Huang · Jing Yang
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Workshop
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Robust Offline Learning via Adversarial World Models
Uljad Berdica · Kelvin Li · Michael Beukman · Alexander D. Goldie · Perla Maiolino · Jakob Foerster
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Workshop
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Order-Optimal Regret in Distributed Kernel Bandits using Uniform Sampling with Shared Randomness
Nikola Pavlovic · Sudeep Salgia · Qing Zhao
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Workshop
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Regulation of Algorithmic Collusion, Refined: Testing Worst-case Calibrated Regret
Jason Hartline · Chang Wang · Chenhao Zhang
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Poster
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Thu 11:00
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Regret Minimization in Stackelberg Games with Side Information
Keegan Harris · Steven Wu · Maria-Florina Balcan
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Workshop
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An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits
Amaury Gouverneur · Borja Rodríguez Gálvez · Tobias Oechtering · Mikael Skoglund
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Poster
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Wed 16:30
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Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
Juliusz Ziomek · Masaki Adachi · Michael A Osborne
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Poster
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Thu 16:30
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Improved Regret for Bandit Convex Optimization with Delayed Feedback
Yuanyu Wan · Chang Yao · Mingli Song · Lijun Zhang
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Poster
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Wed 11:00
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A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of Θ(T2/3) and its Application to Best-of-Both-Worlds
Taira Tsuchiya · Shinji Ito
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Poster
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Fri 11:00
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Is O(log N) practical? Near-Equivalence Between Delay Robustness and Bounded Regret in Bandits and RL
Enoch H. Kang · P. R. Kumar
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