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..
Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?
Authors: Dmitry Metelev, Alexander Rogozin, Dmitry Kovalev, Alexander Gasnikov
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We derive lower communication complexity bounds for several regimes of velocity of networks changes. Moreover, we show how to obtain accelerated communication rates for a certain class of time-varying graphs using a specific consensus algorithm. |
| Researcher Affiliation | Academia | 1Moscow Institute of Physics and Technology, Moscow, Russia 2HSE University, Moscow, Russia 3Universit e Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium 4ISP RAS Research Center for Trusted Artificial Intelligence 5Skolkovo Institute of Science and Technology, Moscow, Russia. |
| Pseudocode | Yes | Algorithm 1 Accelerated Gossip with Non-Recoverable Links |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not describe experiments that would use a dataset for training. |
| Dataset Splits | No | The paper is theoretical and does not conduct experiments, therefore, it does not provide dataset split information for validation. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup or hardware used for computation. |
| Software Dependencies | No | The paper is theoretical and does not describe an experimental setup with specific software dependencies or versions. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with specific hyperparameters or training configurations. |