Multi-Armed Bandits

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 253 papers with code (1,262 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling
  29 Oct 2018 5 repositories listed
  The DRR framework treats recommendation as a sequential decision making procedure and adopts an "Actor-Critic" reinforcement learning scheme to model the interactions between the users and recommender systems, which can…
• Neural Contextual Bandits with UCB-based Exploration
  11 Nov 2019 4 repositories listed
  To the best of our knowledge, it is the first neural network-based contextual bandit algorithm with a near-optimal regret guarantee.
• Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
  26 Feb 2018 4 repositories listed
  At the same time, advances in approximate Bayesian methods have made posterior approximation for flexible neural network models practical.
• Hypothesis Generation with Large Language Models
  5 Apr 2024 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  We focus on hypothesis generation based on data (i.
• Off-Policy Evaluation for Large Action Spaces via Embeddings
  13 Feb 2022 3 repositories listed Syntology ran 1 of 3 samples · 2 unverified
  Unfortunately, when the number of actions is large, existing OPE estimators -- most of which are based on inverse propensity score weighting -- degrade severely and can suffer from extreme bias and variance.
• Online Limited Memory Neural-Linear Bandits with Likelihood Matching
  7 Feb 2021 3 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  To alleviate this, we propose a likelihood matching algorithm that is resilient to catastrophic forgetting and is completely online.
• Gaussian Gated Linear Networks
  10 Jun 2020 3 repositories listed
  We propose the Gaussian Gated Linear Network (G-GLN), an extension to the recently proposed GLN family of deep neural networks.
• Locally Differentially Private (Contextual) Bandits Learning
  1 Jun 2020 3 repositories listed
  We study locally differentially private (LDP) bandits learning in this paper.
• On-line Adaptative Curriculum Learning for GANs
  31 Jul 2018 3 repositories listed
  We argue that less expressive discriminators are smoother and have a general coarse grained view of the modes map, which enforces the generator to cover a wide portion of the data distribution support.
• Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
  4 Dec 2016 3 repositories listed
  We study the off-policy evaluation problem---estimating the value of a target policy using data collected by another policy---under the contextual bandit model.
• Scalable Exploration via Ensemble++
  18 Jul 2024 2 repositories listed Syntology ran 5 of 8 samples · 3 unverified · 8 pointer-only (licence)
  Thompson Sampling is a principled method for balancing exploration and exploitation, but its real-world adoption faces computational challenges in large-scale or non-conjugate settings.
• Generalized Linear Bandits with Limited Adaptivity
  10 Apr 2024 2 repositories listed Syntology ran 10 of 11 samples · 1 unverified · 4 pointer-only (licence)
  We study the generalized linear contextual bandit problem within the constraints of limited adaptivity.
• An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
  9 Nov 2023 2 repositories listed
  This paper addresses both challenges by introducing the Mixture Adaptive Design (MAD), a new experimental design for multi-armed bandit (MAB) algorithms that enables anytime-valid inference on the Average Treatment…
• Kernel Conditional Moment Constraints for Confounding Robust Inference
  26 Feb 2023 2 repositories listed Syntology ran 0 of 17 samples · 17 unverified
  It can be shown that our estimator contains the recently proposed sharp estimator by Dorn and Guo (2022) as a special case, and our method enables a novel extension of the classical marginal sensitivity model using…
• Truncated LinUCB for Stochastic Linear Bandits
  23 Feb 2022 2 repositories listed
  This paper considers contextual bandits with a finite number of arms, where the contexts are independent and identically distributed d-dimensional random vectors, and the expected rewards are linear in both the arm…
• Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
  3 Feb 2022 2 repositories listed
  We show that the proposed estimator is unbiased in more cases compared to existing estimators that make stronger assumptions.
• Empirical analysis of representation learning and exploration in neural kernel bandits
  5 Nov 2021 2 repositories listed
  We consider policies based on a GP and a Student's t-process (TP).
• Inverse Contextual Bandits: Learning How Behavior Evolves over Time
  13 Jul 2021 2 repositories listed
  Understanding a decision-maker's priorities by observing their behavior is critical for transparency and accountability in decision processes, such as in healthcare.
• Quantile Bandits for Best Arms Identification
  22 Oct 2020 2 repositories listed
  We consider a variant of the best arm identification task in stochastic multi-armed bandits.
• Neural Thompson Sampling
  2 Oct 2020 2 repositories listed Syntology ran 6 of 7 samples · 1 unverified · 7 pointer-only (licence)
  Thompson Sampling (TS) is one of the most effective algorithms for solving contextual multi-armed bandit problems.
• Dual-Mandate Patrols: Multi-Armed Bandits for Green Security
  14 Sep 2020 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Conservation efforts in green security domains to protect wildlife and forests are constrained by the limited availability of defenders (i.
• Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting
  18 Jun 2020 2 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  We consider off-policy evaluation in the contextual bandit setting for the purpose of obtaining a robust off-policy selection strategy, where the selection strategy is evaluated based on the value of the chosen policy…
• BanditPAM: Almost Linear Time k-Medoids Clustering via Multi-Armed Bandits
  11 Jun 2020 2 repositories listed Syntology ran 0 of 5 samples · 5 unverified · 5 pointer-only (licence)
  Current state-of-the-art k-medoids clustering algorithms, such as Partitioning Around Medoids (PAM), are iterative and are quadratic in the dataset size n for each iteration, being prohibitively expensive for large…
• The Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many Arms
  24 Feb 2020 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified
  This finding diverges from the notion of free exploration, which relates to covariate variation, as recently discussed in contextual bandit literature.
• A Modern Introduction to Online Learning
  31 Dec 2019 2 repositories listed
  I present first-order and second-order algorithms for online learning with convex losses, in Euclidean and non-Euclidean settings.
• Multi-Armed Bandits with Correlated Arms
  6 Nov 2019 2 repositories listed
  We consider a multi-armed bandit framework where the rewards obtained by pulling different arms are correlated.
• Bayesian Optimisation over Multiple Continuous and Categorical Inputs
  20 Jun 2019 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  Efficient optimisation of black-box problems that comprise both continuous and categorical inputs is important, yet poses significant challenges.
• Intrinsically Efficient, Stable, and Bounded Off-Policy Evaluation for Reinforcement Learning
  9 Jun 2019 2 repositories listed
  We propose new estimators for OPE based on empirical likelihood that are always more efficient than IS, SNIS, and DR and satisfy the same stability and boundedness properties as SNIS.
• Adapting multi-armed bandits policies to contextual bandits scenarios
  11 Nov 2018 2 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  This work explores adaptations of successful multi-armed bandits policies to the online contextual bandits scenario with binary rewards using binary classification algorithms such as logistic regression as black-box…
• SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits
  21 Sep 2018 2 repositories listed
  Motivated by cognitive radio networks, we consider the stochastic multiplayer multi-armed bandit problem, where several players pull arms simultaneously and collisions occur if one of them is pulled by several players…

Syntology lines on 13 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.