He, Chaoyang

13 publications

TMLR 2025 Improving Single-Round Active Adaptation: A Prediction Variability Perspective Xiaoyang Wang, Yibo Jacky Zhang, Olawale Elijah Salaudeen, Mingyuan Wu, Hongpeng Guo, Chaoyang He, Klara Nahrstedt, Sanmi Koyejo

NeurIPS 2023 A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr

TMLR 2023 Distributed Architecture Search over Heterogeneous Distributions Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr

ICMLW 2023 Don’t Memorize; Mimic the past: Federated Class Incremental Learning Without Episodic Memory Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr

AAAI 2023 FairFed: Enabling Group Fairness in Federated Learning Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Amir Salman Avestimehr

NeurIPSW 2023 FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System Weizhao Jin, Yuhang Yao, Shanshan Han, Carlee Joe-Wong, Srivatsan Ravi, Salman Avestimehr, Chaoyang He

ICMLW 2023 Privacy-Preserving Federated Heavy Hitter Analytics for Non-IID Data Jiaqi Shao, Shanshan Han, Chaoyang He, Bing Luo

NeurIPS 2022 FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers, Felix Grimberg, Chaoyang He, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Teleńczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux

AAAI 2022 SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr

FnTML 2021 Advances and Open Problems in Federated Learning Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, 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

NeurIPS 2021 MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin

ICML 2021 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-Scale Models Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr

NeurIPS 2020 Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge Chaoyang He, Murali Annavaram, Salman Avestimehr