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..
Communication Efficient Distributed Newton Method over Unreliable Networks
Authors: Ming Wen, Chengchang Liu, Yuedong Xu
AAAI 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results demonstrate its advantage over first-order and second-order baselines, and its tolerance to packet loss rate ranging from 5% to 40%. |
| Researcher Affiliation | Academia | Ming Wen1, Chengchang Liu2, Yuedong Xu1 1Fudan University, 2The Chinese University of Hong Kong EMAIL, EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: RED-New |
| Open Source Code | No | The paper does not provide any statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | Our experiments are conducted on the benchmark LIBSVM Libraray datasets (Chang and Lin 2011) |
| Dataset Splits | No | The paper mentions using LIBSVM datasets but does not explicitly provide specific training/validation/test dataset split percentages, counts, or cite a predefined split used for reproduction. |
| Hardware Specification | Yes | The experiments are operated on the Intel(R) Xeon(R) Platinum 8369B 2.90GHz, equipped with 32 CPU cores and 2.0TB memory. |
| Software Dependencies | Yes | We conduct our experiments using Python with the Mpy4pi 3.1.4 function for distributed optimization. |
| Experiment Setup | Yes | The learning rate of the proposed methods and the baselines are tuned from {1, 0.1, 0.01, 0.001}. |