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

On the Power of Optimism in Constrained Online Convex Optimization IJCAI 2025
Non-stochastic Budgeted Online Pricing with Semi-Bandit Feedback AAAI 2025
p-Mean Regret for Stochastic Bandits AAAI 2025
Fast Second-Order Online Kernel Learning Through Incremental Matrix Sketching and Decomposition IJCAI 2025
Improved Regret Bounds for Online Fair Division with Bandit Learning AAAI 2025
A Unified Analysis of Nonstochastic Delayed Feedback for Combinatorial Semi-Bandits, Linear Bandits, and MDPs JMLR 2025
Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions AAAI 2025
Score-Aware Policy-Gradient and Performance Guarantees using Local Lyapunov Stability JMLR 2025
Scenario-Based Robust Optimization of Tree Structures AAAI 2025
Safe Online Convex Optimization with Heavy-Tailed Observation Noises AAAI 2025
Batch Ensemble for Variance Dependent Regret in Stochastic Bandits AAAI 2025
No Regret Reinforcement Learning Algorithms for Online Scheduling with Multi-Stage Tasks IJCAI 2025
SMMF: Square-Matricized Momentum Factorization for Memory-Efficient Optimization AAAI 2025
Adaptive Market Making with Inventory Constraints via Online Learning AAAI 2025
Online Nonsubmodular Optimization with Delayed Feedback in the Bandit Setting AAAI 2025
Mixture of Online and Offline Experts for Non-Stationary Time Series AAAI 2025
Decentralized and Uncoordinated Learning of Stable Matchings: A Game-Theoretic Approach AAAI 2025
Efficient Graph Bandit Learning with Side-Observations and Switching Constraints AAAI 2025
Efficient Reinforcement Learning in Probabilistic Reward Machines AAAI 2025
Delay as Payoff in MAB AAAI 2025
Online MDP with Prototypes Information: A Robust Adaptive Approach AAAI 2025
Heterogeneous Multi-Agent Bandits with Parsimonious Hints AAAI 2025
Replication-proof Bandit Mechanism Design with Bayesian Agents AAAI 2025
Problem-dependent Regret for Lexicographic Multi-Armed Bandits with Adversarial Corruptions IJCAI 2025
Neural Combinatorial Clustered Bandits for Recommendation Systems AAAI 2025