Communication Efficient Distributed Newton Method over Unreliable Networks
Authors: Ming Wen, Chengchang Liu, Yuedong Xu
AAAI 2024 | Conference PDF | Archive PDF | Plain Text | 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 mwen23@m.fudan.edu.cn, ccliu22@cse.cuhk.hk, ydxu@fudan.edu.cn |
| 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}. |