# Differential Good Arm Identification

arXiv: https://arxiv.org/abs/2303.07154 · HTML: https://mlsanity.com/paper/2303.07154/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 32 references that are in the map.
- First posted on arXiv 13 Mar 2023.

## Builds on (most cited first, 9 of 9)

- [Neural Tangent Kernel: Convergence and Generalization in Neural Networks](https://mlsanity.com/paper/1806.07572/) (2018)
- [Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks](https://mlsanity.com/paper/1905.13210/) (2019)
- [Finite-Time Analysis of Kernelised Contextual Bandits](https://mlsanity.com/paper/1309.6869/) (2013)
- [Simple Bayesian Algorithms for Best Arm Identification](https://mlsanity.com/paper/1602.08448/) (2016)
- [An optimal algorithm for the Thresholding Bandit Problem](https://mlsanity.com/paper/1605.08671/) (2016)
- [Bootstrapped Thompson Sampling and Deep Exploration](https://mlsanity.com/paper/1507.00300/) (2015)
- [Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits](https://mlsanity.com/paper/1811.05154/) (2018)
- [Good Arm Identification via Bandit Feedback](https://mlsanity.com/paper/1710.06360/) (2017)
- [Differentiable Linear Bandit Algorithm](https://mlsanity.com/paper/2006.03000/) (2020)

## Built on by (most cited first, 8 of 8)

- [Code Less, Align More: Efficient LLM Fine-tuning for Code Generation with Data Pruning](https://mlsanity.com/paper/2407.05040/) (2024)
- [lil'HDoC: An Algorithm for Good Arm Identification under Small Threshold Gap](https://mlsanity.com/paper/2401.15879/) (2024)
- [Enhance the Robustness of Text-Centric Multimodal Alignments](https://mlsanity.com/paper/2407.05036/) (2024)
- [Uncertainty Profiles for LLMs: Uncertainty Source Decomposition and Adaptive Model-Metric Selection](https://mlsanity.com/paper/2505.07309/) (2025)
- [LinearAPT: An Adaptive Algorithm for the Fixed-Budget Thresholding Linear Bandit Problem](https://mlsanity.com/paper/2403.06230/) (2024)
- [Multi-Metric Adaptive Experimental Design Under a Fixed Budget with Validation](https://mlsanity.com/paper/2506.03062/) (2025)
- [Multimodal Chip Physical Design Engineer Assistant](https://mlsanity.com/paper/2510.15872/) (2025)
- [An Efficient Algorithm for Thresholding Monte Carlo Tree Search](https://mlsanity.com/paper/2601.22600/) (2026)

## Abstract (arXiv)

This paper targets a variant of the stochastic multi-armed bandit problem called good arm identification (GAI). GAI is a pure-exploration bandit problem with the goal to output as many good arms using as few samples as possible, where a good arm is defined as an arm whose expected reward is greater than a given threshold. In this work, we propose DGAI - a differentiable good arm identification algorithm to improve the sample complexity of the state-of-the-art HDoC algorithm in a data-driven fashion. We also showed that the DGAI can further boost the performance of a general multi-arm bandit (MAB) problem given a threshold as a prior knowledge to the arm set. Extensive experiments confirm that our algorithm outperform the baseline algorithms significantly in both synthetic and real world datasets for both GAI and MAB tasks.