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..
COKE: Communication-Censored Decentralized Kernel Learning
Authors: Ping Xu, Yue Wang, Xiang Chen, Zhi Tian
JMLR 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Comprehensive tests on both synthetic and real datasets are conducted to verify the communication efficiency and learning effectiveness of COKE.1 |
| Researcher Affiliation | Academia | Ping Xu EMAIL Yue Wang EMAIL Xiang Chen EMAIL Zhi Tian EMAIL Department of Electrical and Computer Engineering, George Mason University Fairfax, VA 22030, USA |
| Pseudocode | Yes | Algorithm 1 DKLA Run at Agent i |
| Open Source Code | No | The paper does not provide explicit information about the availability of open-source code for the methodology described. |
| Open Datasets | Yes | To further evaluate our algorithms, the following popular real-world datasets from UCI machine learning repository are chosen (Asuncion and Newman, 2007). |
| Dataset Splits | Yes | each agent uses 70% of its data for training and the rest for testing. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used to run its experiments. |
| Software Dependencies | No | The paper does not specify any software dependencies with version numbers. |
| Experiment Setup | Yes | The censoring thresholds are h(k) = 0.95k, the regularization parameter λ and stepsize ρ of DKLA and COKE are set to be 5 10 5 and 10 2, respectively. The stepsize of CTA is set to be η = 0.99 |