Is Consensus Acceleration Possible in Decentralized Optimization over Slowly Time-Varying Networks?

Authors: Dmitry Metelev, Alexander Rogozin, Dmitry Kovalev, Alexander Gasnikov

ICML 2023 | Conference PDF | Archive PDF | Plain Text | 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.