conftrace_

adversarial setting

45 papers

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Co-occurring keywords

regret bound (1926) online learning (1777) multi-armed bandit (1098) stochastic setting (12) adversarial learning (1595) online algorithm (445) contextual bandit (381) regret minimization (315) stochastic bandit (98) adversarial bandit (59)

Papers

VestaBench: An Embodied Benchmark for Safe Long-Horizon Planning Under Multi-Constraint and Adversarial Settings EMNLP 2025
Scalable Solutions for Decision-Making Systems Using Explainable Policy Representations AAAI 2025
Faster Recalibration of an Online Predictor via Approachability AISTATS 2024
Regret Minimization in Stackelberg Games with Side Information NIPS 2024
Online Newton Method for Bandit Convex Optimisation Extended Abstract COLT 2024
Bandits with Ranking Feedback NIPS 2024
Pareto Regret Analyses in Multi-objective Multi-armed Bandit ICML 2023
Optimal cross-learning for contextual bandits with unknown context distributions NIPS 2023
Improved Robust Algorithms for Learning with Discriminative Feature Feedback AISTATS 2023
Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation ICML 2023
Delayed Bandits: When Do Intermediate Observations Help? ICML 2023
The Statistical Scope of Multicalibration ICML 2023
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits ICML 2022
Smoothed Adversarial Linear Contextual Bandits with Knapsacks ICML 2022
Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback ICML 2022
The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition NIPS 2021
Online Selective Classification with Limited Feedback NIPS 2021
Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds COLT 2021
Accommodating Picky Customers: Regret Bound and Exploration Complexity for Multi-Objective Reinforcement Learning NIPS 2021
Tsallis-INF for Decoupled Exploration and Exploitation in Multi-armed Bandits COLT 2020
Robust Learning from Discriminative Feature Feedback AISTATS 2020
Thompson Sampling for Adversarial Bit Prediction ALT 2020
Don’t Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases IJCNLP 2019
Best of many worlds: Robust model selection for online supervised learning AISTATS 2019
Dying Experts: Efficient Algorithms with Optimal Regret Bounds NIPS 2019