Publications

Working in Progress

  • DIAMOND: large-scale distributed learning for “vision + language” (grant news coverage)
  • Federated Learning with Personalization/non-I.I.D/Fairness

Preprint

Peer-Reviewed Publications

(I only list my publications with the affiliation of USC)

  • Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
    Chaoyang He, Murali Annavaram, Salman Avestimehr
    (To appear) NeurIPS 2020 (2020 Conference on Neural Information Processing Systems)
    [bib] [arxiv]
    (working on the camera ready revision now)
    Highlights: Efficient large DNN inference on resource-constrained edge (Model Compression) has been well-studied. However, on the other side of the coin, efficient large DNN training on the edge is rarely studied. People even do not aware this is an obstacle for federated learning in practice. This is the early work that attempts to address this challenging problem and raise attention to the entire ML community. Probably, we should call this direction as Training Compression.

  • Advances and Open Problems in Federated Learning
    Peter Kairouz, H Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael GL d’Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adria Gascón, Badih Ghazi, Phillip B Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrede Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X Yu, Han Yu, Sen Zhao
    submitted to FnTML 2020 (Foundations and Trends in Machine Learning), 2020

Patents

Technical Report

  • 2018 – Data-Driven Cloud Computing Platform and Machine Learning System for the Internet of Vehicles
  • 2016 – The Large-Scale Distributed System and Real-Time Location Data Mining
  • 2017 – TAI: An Intelligent Operating System and Open Platform
  • 2016 – Speech Recognition System for Connected and Autonomous Driving Car
  • 2016 – WeGameMap: Real World Map Rendering Engine for Location-Based Mobile Game
  • 2015 – WeLink: a High-Performance Vehicle-Mobile Networking Library
  • 2014 – TMAP: A System Framework for Mobile Maps and Navigation
  • 2016 – Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps
  • 2014 – WeCross: a Mobile and Vehicle C/C++ Cross-Platform Library
  • 2017 – A High Precision Private Car Trajectory Dataset and an Open Source Location Data Computing Platform
  • 2017 – A Open Source High Reliable Location SDK for the Automotive Industry
  • 2013 – The First Generation Mobile Navigation SDK Design in China
  • 2012 – Map State Switching under Multi-trigger Condition Based on Finite State Machine Design Pattern
  • 2012 – A General Downloader Engine for iOS/Android Platform
  • 2012 – The Best Practice for Java Native Interface (JNI) Development on Android Operating Platform
  • 2014 – Taxi-Calling Platform and the Open Source Code
  • 2015 – A UX design of Bluetooth Steering Wheel Wireless Controller and the communication system design
  • 2016 – Sliding Window Algorithm Template to Solve All the Leetcode Substring Search Problem.