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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Does Sparsity Help in Learning Misspecified Linear Bandits?
Authors: Jialin Dong, Lin Yang
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We establish novel algorithms that obtain O(ε)-optimal actions by querying O(ε mdm) actions, where m is the sparsity parameter. For fixed sparsity m, the algorithm finds an O(ε)-optimal action with poly(d/ε) queries, breaking the O(ε d) barrier. We establish information-theoretical lower bounds to show that our upper bounds are nearly tight. |
| Researcher Affiliation | Academia | Department of Electrical and Computer Engineering, University of California, Los Angeles, USA. Correspondence to: Jialin Dong, Lin F. Yang <EMAIL, EMAIL>. |
| Pseudocode | Yes | Algorithm 1 Parameter Elimination (Page 3), Algorithm 2 (ε m)-free Algorithm (Page 4), Algorithm 3 poly(m)-sample-complexity Algorithm (Page 5). |
| Open Source Code | No | The paper does not provide any statement or link indicating the release of open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not involve empirical training on a dataset, nor does it provide access information for any dataset. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splitting for validation. |
| Hardware Specification | No | The paper is theoretical and does not discuss hardware used for any experiments. |
| Software Dependencies | No | The paper is theoretical and does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup, hyperparameters, or training configurations. |