Materials regarding decentralized AI.
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Materials regarding decentralized AI research.

Consensus Optimization

This includes literatures on consensus optimization (mainly from mainly control community). Hopefully one can borrow theory from them to build fully decentralized algorithms.

  • Dual averaging for distributed optimization: Convergence analysis and network scaling
    2012 IEEE Transactions on Automatic control. Duchi, John C and Agarwal, Alekh and Wainwright, Martin J

  • On the convergence of decentralized gradient descent.
    2016 SIAM Journal on Optimization. Yuan, Kun and Ling, Qing and Yin, Wotao

  • DSA: Decentralized double stochastic averaging gradient algorithm
    2016 JMLR. Mokhtari, Aryan and Ribeiro, Alejandro.

Federated Learning & Optimization

This is one recent setting proposed to solve one existing decentralized data setting, but the algorithms therein are still centralized algorithms.

  • Communication-Efficient Learning of Deep Networks from Decentralized Data
    2017 AISTATS. McMahan, Brendan and Moore, Eider and Ramage, Daniel and Hampson, Seth and y Arcas, Blaise Aguera

Mobile AI

This is one emerging setting where one wants to learn an intelligent model for mobile devices, such as mobile phones, tablets etc.

Gossip Algorithm

  • Randomized gossip algorithms
    2006 EEE transactions on information theory. Boyd, Stephen and Ghosh, Arpita and Prabhakar, Balaji and Shah, Devavrat

  • Gossip algorithms
    2009 Foundations and Trends in Networking. Shah, Devavrat



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