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regret bound

2,284 papers

RB

Papers

Adaptive Matrix Online Learning through Smoothing with Guarantees for Nonsmooth Nonconvex Optimization COLT 2026 Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret COLT 2026 Adversarially Robust Multitask Adaptive Control L4DC 2026 Almost sure null bankruptcy of testing-by-betting strategies COLT 2026 A Multi-Agent Conversational Bandit Approach to Online Evaluation and Selection of User-Aligned LLM Responses AAAI 2026 A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design JMLR 2026 A simple, optimal and efficient algorithm for online exp-concave optimization COLT 2026 A Symplectic Analysis of Alternating Mirror Descent JMLR 2026 A Tight Lower Bound for Non-stochastic Multi-armed Bandits with Expert Advice COLT 2026 Avoiding exp($k^*$) Scaling for Thompson Sampling in Combinatorial Semi-Bandits: From Multiple Seeds to a Single Seed COLT 2026 Balancing Expressivity and Learnability in Quantum Kernel Bandit Optimization UAI 2026 Bandit Learning for Online Scheduling with Immediate Decision UAI 2026 Bootstrapping LLMs via Preference-Based Policy Optimization AAAI 2026 Characterizing Online and Private Learnability under Distributional Constraints via Generalized Smoothness COLT 2026 Clipping the Price of Adaptivity at the Tail COLT 2026 Constrained Online Convex Optimization with Memory and Predictions AAAI 2026 Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization UAI 2026 Decentralized Online Convex Optimization with Unknown Feedback Delays AAAI 2026 Distributionally Robust Online Markov Game with Linear Function Approximation AAAI 2026 Distribution-Dependent Rates for Multi-Distribution Learning ALT 2026 Dynamic Regret in Outlier-Oblivious Online Optimization using Nonconvex Robust Losses UAI 2026 ECPv2: Fast, Efficient, and Scalable Global Optimization of Lipschitz Functions AAAI 2026 Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm ALT 2026 Eventually LIL Regret: Almost Sure $\ln\ln T$ Regret for a sub-Gaussian Mixture on Unbounded Data ALT 2026 Exploiting Concavity Information in Contextual Bandit Optimization UAI 2026