Online Algorithms

Barely Random Algorithms and Collective Metrical Task Systems NeurIPS 2024 B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data NeurIPS 2024 Best-of-Both-Worlds Algorithms for Linear Contextual Bandits AISTATS 2024 Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization ICML 2024 Beyond Primal-Dual Methods in Bandits with Stochastic and Adversarial Constraints NeurIPS 2024 Binary Search with Distributional Predictions NeurIPS 2024 Borda Regret Minimization for Generalized Linear Dueling Bandits ICML 2024 Burstable Cloud Block Storage with Data Processing Units OSDI 2024 Can Probabilistic Feedback Drive User Impacts in Online Platforms? AISTATS 2024 CASSINI: Network-Aware Job Scheduling in Machine Learning Clusters NSDI 2024 Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals ICML 2024 Chasing Convex Functions with Long-term Constraints ICML 2024 Communication Bounds for the Distributed Experts Problem NeurIPS 2024 Computing Optimal Equilibria in Repeated Games with Restarts IJCAI 2024 Confounded Budgeted Causal Bandits CLeaR 2024 Consistent Submodular Maximization ICML 2024 Contextual Bandits with Budgeted Information Reveal AISTATS 2024 Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression JMLR 2024 Contextual Decision-Making with Knapsacks Beyond the Worst Case NeurIPS 2024 Contextual Linear Optimization with Bandit Feedback NeurIPS 2024 Contextual Multinomial Logit Bandits with General Value Functions NeurIPS 2024 Contextual Pandora’s Box AAAI 2024 Continual Counting with Gradual Privacy Expiration NeurIPS 2024 Continuous Prediction with Experts' Advice JMLR 2024 Contract Scheduling with Distributional and Multiple Advice IJCAI 2024