regret bound

Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication AISTATS 2024 Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit ICLR 2024 Contextual Active Model Selection NeurIPS 2024 Contextual Bandits with Online Neural Regression ICLR 2024 Contextual Decision-Making with Knapsacks Beyond the Worst Case NeurIPS 2024 Contextual Linear Optimization with Bandit Feedback NeurIPS 2024 Contextual Multinomial Logit Bandits with General Value Functions NeurIPS 2024 Convergence of Bayesian Bilevel Optimization ICLR 2024 Convergence of No-Swap-Regret Dynamics in Self-Play NeurIPS 2024 Convergence to Nash Equilibrium and No-regret Guarantee in (Markov) Potential Games AISTATS 2024 Corruption-Robust Lipschitz Contextual Search ALT 2024 CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption ALT 2024 Decentralized Scheduling with QoS Constraints: Achieving O(1) QoS Regret of Multi-Player Bandits AAAI 2024 Decentralized Two-Sided Bandit Learning in Matching Market UAI 2024 Demystifying Linear MDPs and Novel Dynamics Aggregation Framework ICLR 2024 Differentially Private No-regret Exploration in Adversarial Markov Decision Processes UAI 2024 Differentially Private Reinforcement Learning with Self-Play NeurIPS 2024 Directional Optimism for Safe Linear Bandits AISTATS 2024 Dueling Optimization with a Monotone Adversary ALT 2024 Dynamic Budget Throttling in Repeated Second-Price Auctions AAAI 2024 Dynamic Service Fee Pricing under Strategic Behavior: Actions as Instruments and Phase Transition NeurIPS 2024 Efficient Exploration in Average-Reward Constrained Reinforcement Learning: Achieving Near-Optimal Regret With Posterior Sampling ICML 2024 Efficient Interactive Maximization of BP and Weakly Submodular Objectives UAI 2024 Efficient Learning in Polyhedral Games via Best-Response Oracles AAAI 2024 Ensemble sampling for linear bandits: small ensembles suffice NeurIPS 2024