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Online Algorithms

2,192 papers

Papers per year

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Papers

FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms ACL 2019
Efficient Linear Bandits through Matrix Sketching AISTATS 2019
Logarithmic Regret for Online Gradient Descent Beyond Strong Convexity AISTATS 2019
Lifelong Optimization with Low Regret AISTATS 2019
Optimal Testing in the Experiment-rich Regime AISTATS 2019
Active Exploration in Markov Decision Processes AISTATS 2019
Bandit Online Learning with Unknown Delays AISTATS 2019
Projection Free Online Learning over Smooth Sets AISTATS 2019
Finding the bandit in a graph: Sequential search-and-stop AISTATS 2019
MaxHedge: Maximizing a Maximum Online AISTATS 2019
Regularized Contextual Bandits AISTATS 2019
Consistent Online Optimization: Convex and Submodular AISTATS 2019
Online learning with feedback graphs and switching costs AISTATS 2019
Online Algorithm for Unsupervised Sensor Selection AISTATS 2019
Best of many worlds: Robust model selection for online supervised learning AISTATS 2019
Online Learning in Kernelized Markov Decision Processes AISTATS 2019
On Learning Graphs with Edge-Detecting Queries ALT 2019
Competitive ratio vs regret minimization: achieving the best of both worlds ALT 2019
PAC Battling Bandits in the Plackett-Luce Model ALT 2019
Learning to Prune: Speeding up Repeated Computations COLT 2019
Adaptively Tracking the Best Bandit Arm with an Unknown Number of Distribution Changes COLT 2019
Achieving Optimal Dynamic Regret for Non-stationary Bandits without Prior Information COLT 2019
Sorted Top-k in Rounds COLT 2019
Improved Path-length Regret Bounds for Bandits COLT 2019
On the Computational Power of Online Gradient Descent COLT 2019