← Learning Types
Machine Learning › Learning Types ›

Multi-Armed Bandits

1044 directly classified papers

Papers per year

Papers

Parametric Graph for Unimodal Ranking Bandit ICML 2021
Top-k eXtreme Contextual Bandits with Arm Hierarchy ICML 2021
Optimal regret algorithm for Pseudo-1d Bandit Convex Optimization ICML 2021
Stochastic Linear Bandits Robust to Adversarial Attacks AISTATS 2021
Dueling Convex Optimization ICML 2021
Adversarial Dueling Bandits ICML 2021
Best Arm Identification in Graphical Bilinear Bandits ICML 2021
Leveraging Good Representations in Linear Contextual Bandits ICML 2021
Sparsity-Agnostic Lasso Bandit ICML 2021
Online Limited Memory Neural-Linear Bandits with Likelihood Matching ICML 2021
Confidence-Budget Matching for Sequential Budgeted Learning ICML 2021
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning ICML 2021
Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions ICML 2021
Bandit Learning with Delayed Impact of Actions NIPS 2021
Bias-Robust Bayesian Optimization via Dueling Bandits ICML 2021
MOTS: Minimax Optimal Thompson Sampling ICML 2021
Federated Linear Contextual Bandits NIPS 2021
Almost Optimal Anytime Algorithm for Batched Multi-Armed Bandits ICML 2021
Optimal Streaming Algorithms for Multi-Armed Bandits ICML 2021
Reserve Price Optimization for First Price Auctions in Display Advertising ICML 2021
Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization ICML 2021
Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing ICML 2021
The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle NIPS 2021
High-dimensional Experimental Design and Kernel Bandits ICML 2021
Offline Contextual Bandits with Overparameterized Models ICML 2021