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..
Efficient Algorithms for General Isotone Optimization
Authors: Xiwen Wang, Jiaxi Ying, José Vinícius de M. Cardoso, Daniel P. Palomar8575-8583
AAAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate our algorithm and state-of-the-art methods with experiments involving both synthetic and real-world data. The experimental results demonstrate that our algorithm is more efficient by one to four orders of magnitude than the state-of-the-art methods. |
| Researcher Affiliation | Academia | Xiwen Wang, Jiaxi Ying, Jos e Vin ıcius de M. Cardoso, Daniel P. Palomar The Hong Kong University of Science and Technology EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: Sequential block merging (SBM). |
| Open Source Code | Yes | The code is available in https://github.com/Xiwen1997/Isotone Optimization. |
| Open Datasets | Yes | To illustrate the practicality of our method in real-world applications, we use the Adult data set, available from the UCI Machine Learning repository. |
| Dataset Splits | No | The paper mentions using 'randomly generated data sets, with the initial violating rate around 20 50%' for synthetic data, and the 'Adult data set' for real data, but does not provide specific training, validation, or test split percentages or sample counts. |
| Hardware Specification | No | The paper does not specify any hardware components (e.g., CPU, GPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper mentions benchmark software like 'isotone', 'quadprog', 'IRP', and 'IPM' but does not provide version numbers for these or any other software dependencies used for their implementation. |
| Experiment Setup | Yes | We set λ = 20, ϵ = 0.1, p = 302, and step size η = 5 × 10−4. |