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Online Algorithms

806 papers

Papers per year

6
24
87
21
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Papers

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
Budgeted Online Influence Maximization ICML 2020
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound ICML 2020
Neural Contextual Bandits with UCB-based Exploration 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
Memoryless Sequences for General Losses JMLR 2020
Dynamic Assortment Optimization with Changing Contextual Information JMLR 2020
Randomized Exploration for Non-Stationary Stochastic Linear Bandits UAI 2020
A Simple Online Algorithm for Competing with Dynamic Comparators UAI 2020
A SUPER* Algorithm to Optimize Paper Bidding in Peer Review UAI 2020
Online Parameter-Free Learning of Multiple Low Variance Tasks UAI 2020
Semi-bandit Optimization in the Dispersed Setting UAI 2020
Batched Multi-armed Bandits Problem NIPS 2019
Learning to Screen NIPS 2019
Bootstrapping Upper Confidence Bound NIPS 2019
Private Learning Implies Online Learning: An Efficient Reduction NIPS 2019
Logarithmic Regret for Online Control NIPS 2019