← Optimization
Mathematics & Optimization › Optimization ›

Online Algorithms

2190 directly classified papers

Papers per year

Papers

Learning from a Sample in Online Algorithms NIPS 2022
Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor NIPS 2022
Online Allocation and Learning in the Presence of Strategic Agents NIPS 2022
Delay-Adaptive Step-sizes for Asynchronous Learning ICML 2022
Efficient and Near-Optimal Smoothed Online Learning for Generalized Linear Functions NIPS 2022
Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs NIPS 2022
Real-Time Driver-Request Assignment in Ridesourcing AAAI 2022
Online Page Migration with ML Advice AISTATS 2022
The Two-Sided Game of Googol JMLR 2022
Oracle-Efficient Online Learning for Smoothed Adversaries NIPS 2022
Damped Online Newton Step for Portfolio Selection COLT 2022
A gradient estimator via L1-randomization for online zero-order optimization with two point feedback NIPS 2022
The Metric Distortion of Multiwinner Voting AAAI 2022
Learning-Augmented Algorithms for Online Steiner Tree AAAI 2022
Nonstochastic Bandits with Composite Anonymous Feedback JMLR 2022
Best of Both Worlds Model Selection NIPS 2022
No Weighted-Regret Learning in Adversarial Bandits with Delays JMLR 2022
Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search NIPS 2022
Donar: Anonymous VoIP over Tor NSDI 2022
Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case JMLR 2022
PopArt: Efficient Sparse Regression and Experimental Design for Optimal Sparse Linear Bandits NIPS 2022
Collaborative Linear Bandits with Adversarial Agents: Near-Optimal Regret Bounds NIPS 2022
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism JMLR 2022
Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms NIPS 2022
An $\alpha$-regret analysis of Adversarial Bilateral Trade NIPS 2022