conftrace_

regret bound

1926 papers

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Also known as

RB

Co-occurring keywords

online learning (1777) multi-armed bandit (1098) contextual bandit (381) stochastic optimization (1060) reinforcement learning (4352) online algorithm (445) upper confidence bound (197) markov decision process (790) thompson sampling (237) online convex optimization (165)

Papers

Monte Carlo Tree Search in the Presence of Transition Uncertainty AAAI 2024
Federated X-armed Bandit AAAI 2024
Online Restless Multi-Armed Bandits with Long-Term Fairness Constraints AAAI 2024
Safe Exploitative Play with Untrusted Type Beliefs NIPS 2024
Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users AAAI 2024
Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation NIPS 2024
Consistent Hierarchical Classification with A Generalized Metric AISTATS 2024
Concentration Tail-Bound Analysis of Coevolutionary and Bandit Learning Algorithms IJCAI 2024
Faster Recalibration of an Online Predictor via Approachability AISTATS 2024
Oracle-Efficient Hybrid Online Learning with Unknown Distribution COLT 2024
Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits? COLT 2024
On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UX AISTATS 2024
Online Control with Adversarial Disturbance for Continuous-time Linear Systems NIPS 2024
Combinatorial Stochastic-Greedy Bandit AAAI 2024
Causal Bandits with General Causal Models and Interventions AISTATS 2024
Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources AISTATS 2024
Tight Rates for Bandit Control Beyond Quadratics NIPS 2024
Fully Unconstrained Online Learning NIPS 2024
Conformal Inference for Online Prediction with Arbitrary Distribution Shifts JMLR 2024
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion AISTATS 2024
A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent AISTATS 2024
Mitigating Underfitting in Learning to Defer with Consistent Losses AISTATS 2024
Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment JMLR 2024
No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints AISTATS 2024
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs NIPS 2024