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Multi-Armed Bandits

Multi-armed bandits refer to a task where a fixed amount of resources must be allocated between competing resources that maximizes expected gain. Typically these problems involve an exploration/exploitation trade-off.

( Image credit: Microsoft Research )

Papers

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Showing 301–350 of 1262 papers

TitleStatusHype
Contextual Combinatorial Multi-armed Bandits with Volatile Arms and Submodular Reward—0
A conversion theorem and minimax optimality for continuum contextual bandits—0
Contextual Information-Directed Sampling—0
Contextual Linear Bandits with Delay as Payoff—0
Contextual memory bandit for pro-active dialog engagement—0
Contextual Multi-Armed Bandits for Causal Marketing—0
Bandits Don’t Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits—0
Contextual Multinomial Logit Bandits with General Value Functions—0
Contextual Online Decision Making with Infinite-Dimensional Functional Regression—0
Contextual Pandora's Box—0
Contextual Restless Multi-Armed Bandits with Application to Demand Response Decision-Making—0
Context Uncertainty in Contextual Bandits with Applications to Recommender Systems—0
Continuous K-Max Bandits—0
Continuous-Time Multi-Armed Bandits with Controlled Restarts—0
Convex Hull Monte-Carlo Tree Search—0
Cooperative Multi-agent Bandits: Distributed Algorithms with Optimal Individual Regret and Constant Communication Costs—0
Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions—0
Coordinated Attacks against Contextual Bandits: Fundamental Limits and Defense Mechanisms—0
Contexts can be Cheap: Solving Stochastic Contextual Bandits with Linear Bandit Algorithms—0
Coordination without communication: optimal regret in two players multi-armed bandits—0
Bandits with Partially Observable Confounded Data—0
CorrAttack: Black-box Adversarial Attack with Structured Search—0
Bandits with Temporal Stochastic Constraints—0
Almost Boltzmann Exploration—0
Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes—0
Corruption-robust exploration in episodic reinforcement learning—0
Context-Aware Bandits—0
Banker Online Mirror Descent: A Universal Approach for Delayed Online Bandit Learning—0
Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models—0
Query-Reward Tradeoffs in Multi-Armed Bandits—0
Data Acquisition for Improving Model Fairness using Reinforcement Learning—0
Data Dependent Regret Guarantees Against General Comparators for Full or Bandit Feedback—0
Data-Driven Upper Confidence Bounds with Near-Optimal Regret for Heavy-Tailed Bandits—0
Data Poisoning Attacks in Contextual Bandits—0
Data Poisoning Attacks on Stochastic Bandits—0
DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees—0
Batched Nonparametric Bandits via k-Nearest Neighbor UCB—0
Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure—0
Asymptotic Performance of Thompson Sampling in the Batched Multi-Armed Bandits—0
Decentralized Exploration in Multi-Armed Bandits -- Extended version—0
Decentralized Upper Confidence Bound Algorithms for Homogeneous Multi-Agent Multi-Armed Bandits—0
Decentralized Multi-player Multi-armed Bandits with No Collision Information—0
Decentralized Smart Charging of Large-Scale EVs using Adaptive Multi-Agent Multi-Armed Bandits—0
Decision Automation for Electric Power Network Recovery—0
Scalable Decision-Focused Learning in Restless Multi-Armed Bandits with Application to Maternal and Child Health—0
Decision Making in Changing Environments: Robustness, Query-Based Learning, and Differential Privacy—0
Asymptotic Instance-Optimal Algorithms for Interactive Decision Making—0
Batch Ensemble for Variance Dependent Regret in Stochastic Bandits—0
Deep Contextual Bandits for Fast Neighbor-Aided Initial Access in mmWave Cell-Free Networks—0
Constrained Pure Exploration Multi-Armed Bandits with a Fixed Budget—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NeuralLinear FullPosterior-MRCumulative regret1.92—Unverified
2Linear FullPosterior-MRCumulative regret1.82—Unverified