← Optimization
Mathematics & Optimization › Optimization ›

Online Algorithms

2190 directly classified papers

Papers per year

Papers

Selective Sampling for Online Best-arm Identification NIPS 2021
Making the most of your day: online learning for optimal allocation of time NIPS 2021
Online Adaptation to Label Distribution Shift NIPS 2021
Sequential Algorithms for Testing Closeness of Distributions NIPS 2021
Variational Bayesian Optimistic Sampling NIPS 2021
Learning in Multi-Stage Decentralized Matching Markets NIPS 2021
Revisiting Smoothed Online Learning NIPS 2021
Online Selective Classification with Limited Feedback NIPS 2021
Fast Routing under Uncertainty: Adaptive Learning in Congestion Games via Exponential Weights NIPS 2021
Learning-to-learn non-convex piecewise-Lipschitz functions NIPS 2021
Doubly Robust Thompson Sampling with Linear Payoffs NIPS 2021
Multi-armed Bandit Requiring Monotone Arm Sequences NIPS 2021
Information Directed Sampling for Sparse Linear Bandits NIPS 2021
The Pareto Frontier of model selection for general Contextual Bandits NIPS 2021
A Unified Approach to Fair Online Learning via Blackwell Approachability NIPS 2021
Efficient First-Order Contextual Bandits: Prediction, Allocation, and Triangular Discrimination NIPS 2021
Multi-Armed Bandits with Bounded Arm-Memory: Near-Optimal Guarantees for Best-Arm Identification and Regret Minimization NIPS 2021
Asynchronous Decentralized Online Learning NIPS 2021
Best-case lower bounds in online learning NIPS 2021
Asymptotically Best Causal Effect Identification with Multi-Armed Bandits NIPS 2021
Bandits with Knapsacks beyond the Worst Case NIPS 2021
Recurrent Submodular Welfare and Matroid Blocking Semi-Bandits NIPS 2021
Mixability made efficient: Fast online multiclass logistic regression NIPS 2021
Fair Algorithms for Multi-Agent Multi-Armed Bandits NIPS 2021
An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints NIPS 2021