Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Instance-Sensitive Algorithms for Pure Exploration in Multinomial Logit Bandit
Authors: Nikolai Karpov, Qin Zhang7096-7103
AAAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we give efficient algorithms for pure exploration in MNL-bandit. Our algorithms achieve instancesensitive pull complexities. We also complement the upper bounds by an almost matching lower bound. |
| Researcher Affiliation | Academia | Indiana University Bloomington Luddy Hall, RM 3044 700 North Woodlawn Avenue Bloomington, IN 47408-3901, USA EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: EXPLORE(i) ... Algorithm 2: PRUNE(I, K, a, b) ... Algorithm 3: The Fixed Confidence Algorithm for MNL-Bandit ... Algorithm 4: EXPLORESET(S) ... Algorithm 5: Improved Fixed Confidence Algorithm for MNL-bandit |
| Open Source Code | No | The paper does not provide any statement or link indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments on a dataset, thus it does not mention a training dataset. |
| Dataset Splits | No | The paper is theoretical and does not conduct experiments on a dataset, thus it does not mention training, validation, or test splits. |
| Hardware Specification | No | The paper is theoretical and focuses on algorithms and complexity, without discussing the hardware used for any computational tasks. |
| Software Dependencies | No | The paper is theoretical and describes algorithms, but it does not mention any specific software dependencies or version numbers. |
| Experiment Setup | No | The paper describes theoretical algorithms and their complexities but does not detail an experimental setup, as no empirical experiments are reported. |