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..
Rate-Optimal Online Convex Optimization in Adaptive Linear Control
Authors: Asaf Benjamin Cassel, Alon Peled-Cohen, Tomer Koren
NeurIPS 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The proof is deferred to the full version of the paper [16]. When asked 'Did you run experiments?', the paper states 'N/A' for all sub-questions related to experiments, indicating a purely theoretical work. |
| Researcher Affiliation | Collaboration | Blavatnik School of Computer Science, Tel Aviv University; EMAIL. School of Electrical Engineering, Tel Aviv University, and Google Tel Aviv; EMAIL. Blavatnik School of Computer Science, Tel Aviv University, Google Tel Aviv; EMAIL. |
| Pseudocode | Yes | Algorithm 1 OCO in Adaptive Linear Control; Algorithm 2 OCO with a hidden linear transform. |
| Open Source Code | No | The paper states 'N/A' for including code, data, and instructions needed to reproduce main experimental results, and no explicit statement or link for open-source code is provided. |
| Open Datasets | No | The paper is theoretical and does not involve experiments with datasets. |
| Dataset Splits | No | The paper is theoretical and does not involve dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper states 'N/A' for hardware specifications in its self-assessment. No specific hardware details are mentioned in the text. |
| Software Dependencies | No | The paper is theoretical and does not specify software dependencies with version numbers for reproducibility. |
| Experiment Setup | No | The paper states 'N/A' for specifying training details like hyperparameters. It is a theoretical paper and does not include details on experimental setup. |