regret minimization

Satisficing Regret Minimization in Bandits ICLR 2025 A Doubly Robust Approach to Sparse Reinforcement Learning AISTATS 2024 Adversarial Environment Design via Regret-Guided Diffusion Models NeurIPS 2024 A representation-learning game for classes of prediction tasks ICLR 2024 A Simple and Optimal Approach for Universal Online Learning with Gradient Variations NeurIPS 2024 Autoregressive Bandits AISTATS 2024 Beating Adversarial Low-Rank MDPs with Unknown Transition and Bandit Feedback NeurIPS 2024 Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints NeurIPS 2024 Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies ICLR 2024 Communication-Efficient Collaborative Regret Minimization in Multi-Armed Bandits AAAI 2024 Confounded Budgeted Causal Bandits CLeaR 2024 Convergence of No-Swap-Regret Dynamics in Self-Play NeurIPS 2024 Directional Optimism for Safe Linear Bandits AISTATS 2024 Dynamic Budget Throttling in Repeated Second-Price Auctions AAAI 2024 Efficient Φ-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games NeurIPS 2024 Efficient Learning in Polyhedral Games via Best-Response Oracles AAAI 2024 Eluder-based Regret for Stochastic Contextual MDPs ICML 2024 Extensive-Form Game Solving via Blackwell Approachability on Treeplexes NeurIPS 2024 Improving Environment Novelty Quantification for Effective Unsupervised Environment Design NeurIPS 2024 Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms NeurIPS 2024 Learning Not to Regret AAAI 2024 Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery ICML 2024 Meta Learning in Bandits within shared affine Subspaces AISTATS 2024 Multi-Agent Imitation Learning: Value is Easy, Regret is Hard NeurIPS 2024 Mutli-Armed Bandits with Network Interference NeurIPS 2024