← Optimization
Mathematics & Optimization › Optimization ›

Online Algorithms

2190 directly classified papers

Papers per year

Papers

Approximate Function Evaluation via Multi-Armed Bandits AISTATS 2022
Learning to Plan Variable Length Sequences of Actions with a Cascading Bandit Click Model of User Feedback AISTATS 2022
Contextual Bandits with Large Action Spaces: Made Practical ICML 2022
A Simple yet Universal Strategy for Online Convex Optimization ICML 2022
PDE-Based Optimal Strategy for Unconstrained Online Learning ICML 2022
Learning from a Learning User for Optimal Recommendations ICML 2022
Linear Bandit Algorithms with Sublinear Time Complexity ICML 2022
A Difference Standardization Method for Mutual Transfer Learning ICML 2022
Smoothed Adversarial Linear Contextual Bandits with Knapsacks ICML 2022
Instance Dependent Regret Analysis of Kernelized Bandits ICML 2022
Optimal and Efficient Dynamic Regret Algorithms for Non-Stationary Dueling Bandits ICML 2022
One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes ICML 2022
Universal and data-adaptive algorithms for model selection in linear contextual bandits ICML 2022
Nested Bandits ICML 2022
Multi-slots Online Matching with High Entropy ICML 2022
Equivalence Analysis between Counterfactual Regret Minimization and Online Mirror Descent ICML 2022
Online Nonsubmodular Minimization with Delayed Costs: From Full Information to Bandit Feedback ICML 2022
Decentralized Online Convex Optimization in Networked Systems ICML 2022
Online Learning and Pricing with Reusable Resources: Linear Bandits with Sub-Exponential Rewards ICML 2022
Adaptive Best-of-Both-Worlds Algorithm for Heavy-Tailed Multi-Armed Bandits ICML 2022
Deep Hierarchy in Bandits ICML 2022
A Reduction from Linear Contextual Bandits Lower Bounds to Estimations Lower Bounds ICML 2022
No-Regret Learning in Partially-Informed Auctions ICML 2022
Breaking the $\sqrtT$ Barrier: Instance-Independent Logarithmic Regret in Stochastic Contextual Linear Bandits ICML 2022
A Regret Minimization Approach to Multi-Agent Control ICML 2022