conftrace_

multi-armed bandit

1098 papers

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Also known as

MAB

Co-occurring keywords

regret bound (1926) online learning (1777) stochastic optimization (1060) thompson sampling (237) upper confidence bound (197) regret minimization (315) online algorithm (445) sample complexity (1169) contextual bandit (381) best arm identification (85)

Papers

Automated Curriculum Learning for Neural Networks ICML 2017
Online Learning to Rank in Stochastic Click Models ICML 2017
Multi-objective Bandits: Optimizing the Generalized Gini Index ICML 2017
On Context-Dependent Clustering of Bandits ICML 2017
Gaussian Process Bandit Optimisation with Multi-fidelity Evaluations NIPS 2016
Double Thompson Sampling for Dueling Bandits NIPS 2016
On Explore-Then-Commit strategies NIPS 2016
Causal Bandits: Learning Good Interventions via Causal Inference NIPS 2016
Multi-Player Bandits – a Musical Chairs Approach ICML 2016
Pricing a Low-regret Seller ICML 2016
An optimal algorithm for the Thresholding Bandit Problem ICML 2016
BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits ICML 2016
Multi-armed Bandits: Competing with Optimal Sequences NIPS 2016
Combinatorial Multi-Armed Bandit with General Reward Functions NIPS 2016
Non-stochastic Best Arm Identification and Hyperparameter Optimization AISTATS 2016
Time-Varying Gaussian Process Bandit Optimization AISTATS 2016
Online Learning with Feedback Graphs Without the Graphs ICML 2016
Best-of-K-bandits COLT 2016
Maximin Action Identification: A New Bandit Framework for Games COLT 2016
Optimal Best Arm Identification with Fixed Confidence COLT 2016
The Multi-fidelity Multi-armed Bandit NIPS 2016
Refined Lower Bounds for Adversarial Bandits NIPS 2016
Importance Weighting Without Importance Weights: An Efficient Algorithm for Combinatorial Semi-Bandits JMLR 2016
Combinatorial Multi-Armed Bandit and Its Extension to Probabilistically Triggered Arms JMLR 2016
Tracking the Best Expert in Non-stationary Stochastic Environments NIPS 2016