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Online Algorithms

803 directly classified papers

Papers per year

Papers

An Optimal Algorithm for Adversarial Bandits with Arbitrary Delays AISTATS 2020
Contextual Online False Discovery Rate Control AISTATS 2020
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits AISTATS 2020
A Reduction from Reinforcement Learning to No-Regret Online Learning AISTATS 2020
Memoryless Sequences for General Losses JMLR 2020
Online Decision Based Visual Tracking via Reinforcement Learning NIPS 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020
Dynamic Assortment Optimization with Changing Contextual Information JMLR 2020
Online Learning with Dependent Stochastic Feedback Graphs ICML 2020
Real-Time Optimisation for Online Learning in Auctions ICML 2020
Parameter-free, Dynamic, and Strongly-Adaptive Online Learning ICML 2020
Logarithmic Regret for Adversarial Online Control ICML 2020
No-Regret and Incentive-Compatible Online Learning ICML 2020
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020
Neural Contextual Bandits with UCB-based Exploration ICML 2020
Improved Regret Bounds for Projection-free Bandit Convex Optimization AISTATS 2020
Online Learning with Continuous Variations: Dynamic Regret and Reductions AISTATS 2020
An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss AISTATS 2020
Online Learning with Imperfect Hints ICML 2020
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound ICML 2020
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation IJCAI 2020
Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space IJCAI 2020
Trade the System Efficiency for the Income Equality of Drivers in Rideshare IJCAI 2020
A Unified Model for the Two-stage Offline-then-Online Resource Allocation IJCAI 2020
Efficient and Robust High-Dimensional Linear Contextual Bandits IJCAI 2020