Verification Based Solution for Structured MAB Problems
Authors: Zohar S. Karnin
NeurIPS 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We consider the problem of finding the best arm in a stochastic Multi-armed Bandit (MAB) game and propose a general framework based on verification that applies to multiple well-motivated generalizations of the classic MAB problem. Our results are focused on the scenario where the failure probability δ must be very low; we essentially show that in this high confidence regime, identifying the best arm is as easy as the task of verification. |
| Researcher Affiliation | Industry | Zohar Karnin Yahoo Research New York, NY 10036 zkarnin@ymail.com |
| Pseudocode | Yes | Algorithm 1 Explore-Verify Framework |
| Open Source Code | No | The paper is theoretical and does not mention the release of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and focuses on algorithmic frameworks and complexity analysis, not empirical evaluation. It does not mention or provide access information for any publicly available or open datasets. |
| Dataset Splits | No | The paper is theoretical and does not describe empirical experiments involving dataset splits (training, validation, test). |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not include details on experimental setup, such as hyperparameters or system-level training settings. |