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Efficient Distributed Optimization Algorithms for Digital-twin Computing

Project Member(s): Zhang, G.

Funding or Partner Organisation: Nippon Telegraph and Telephone Corporation
Nippon Telegraph and Telephone Corporation

Start year: 2020

Summary: This project intends to develop novel distributed optimization algorithms for digital-twin computing which refers to the framework of creating and learning digital models to mimic the behaviors of real-world entities (e.g., driving a car or playing a video game).


Niwa, K, Zhang, G, Kleijn, WB, Harada, N, Sawada, H & Fujino, A 1970, 'Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction', Proceedings of Machine Learning Research, virtual conference, pp. 8195-8204.

FOR Codes: Optimisation , Expanding Knowledge in the Mathematical Sciences, Optimisation, Knowledge Representation and Machine Learning, Machine learning