Chaoyang He

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 63

Top Topics

Bipartite Graph

Natural Language

Neural Architecture

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Publications

Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, Wenxuan Wu, Chulin Xie, Yuhang Yao, Kai Zhang, Qifan Zhang, Yuhui Zhang, Carlee Joe-Wong, Salman Avestimehr, Chaoyang He
FedSecurity: A Benchmark for Attacks and Defenses in Federated Learning and Federated LLMs. KDD (2024)
Shanshan Han, Qifan Zhang, Yuhang Yao, Weizhao Jin, Zhaozhuo Xu, Chaoyang He
LLM Multi-Agent Systems: Challenges and Open Problems. CoRR (2024)
Shanshan Han, Yuhang Yao, Zijian Hu, Dimitris Stripelis, Zhaozhuo Xu, Chaoyang He
TorchOpera: A Compound AI System for LLM Safety. CoRR (2024)
Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. NeurIPS (2023)
Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
Partial model averaging in Federated Learning: Performance guarantees and benefits. Neurocomputing 556 (2023)
Haishan Ye, Chaoyang He, Xiangyu Chang
Accelerated Distributed Approximate Newton Method. IEEE Trans. Neural Networks Learn. Syst. 34 (11) (2023)
Baturalp Buyukates, Chaoyang He, Shanshan Han, Zhiyong Fang, Yupeng Zhang, Jieyi Long, Ali Farahanchi, Salman Avestimehr
Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain. CoRR (2023)
Weizhao Jin, Yuhang Yao, Shanshan Han, Carlee Joe-Wong, Srivatsan Ravi, Salman Avestimehr, Chaoyang He
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System. CoRR (2023)
Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr
Distributed Architecture Search Over Heterogeneous Distributions. Trans. Mach. Learn. Res. 2023 (2023)
Han Huang, Li Shen, Chaoyang He, Weisheng Dong, Wei Liu
Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution. IEEE Trans. Circuits Syst. Video Technol. 33 (6) (2023)
Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Amir Salman Avestimehr
FairFed: Enabling Group Fairness in Federated Learning. AAAI (2023)
Shanshan Han, Baturalp Buyukates, Zijian Hu, Han Jin, Weizhao Jin, Lichao Sun, Xiaoyang Wang, Chulin Xie, Kai Zhang, Qifan Zhang, Yuhui Zhang, Chaoyang He, Salman Avestimehr
FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs. CoRR (2023)
Ahmed Roushdy Elkordy, Yahya H. Ezzeldin, Shanshan Han, Shantanu Sharma, Chaoyang He, Sharad Mehrotra, Salman Avestimehr
Federated Analytics: A survey. CoRR (2023)
Tian Xie, Chaoyang He, Xiang Ren, Cyrus Shahabi, C.-C. Jay Kuo
L-BGNN: Layerwise Trained Bipartite Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 34 (12) (2023)
Sunwoo Lee, Chaoyang He, Salman Avestimehr
Achieving small-batch accuracy with large-batch scalability via Hessian-aware learning rate adjustment. Neural Networks 158 (2023)
Baturalp Buyukates, Chaoyang He, Shanshan Han, Zhiyong Fang, Yupeng Zhang, Jieyi Long, Ali Farahanchi, Salman Avestimehr
Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain. DAPPS (2023)
Shen Li, Pritam Damania, Luca Wehrstedt, Rohan Varma, Omkar Salpekar, Pavel Belevich, Howard Huang, Yanli Zhao, Lucas Hosseini, Wanchao Liang, Hongyi Jia, Shihao Xu, Satendra Gera, Alisson G. Azzolini, Guoqiang Jerry Chen, Zachary DeVito, Chaoyang He, Amir Ziashahabi, Alban Desmaison, Edward Z. Yang, Gregory Chanan, Brian Vaughan, Manoj Krishnan, Joseph S. Spisak, Salman Avestimehr, Soumith Chintala
PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. MLSys (2023)
Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory. CoRR (2023)
Zhenheng Tang, Xiaowen Chu, Ryan Yide Ran, Sunwoo Lee, Shaohuai Shi, Yonggang Zhang, Yuxin Wang, Alex Qiaozhong Liang, Salman Avestimehr, Chaoyang He
FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training. CoRR (2023)
Jiaqi Shao, Shanshan Han, Chaoyang He, Bing Luo
Privacy-Preserving Federated Heavy Hitter Analytics for Non-IID Data. CoRR (2023)
Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks. CoRR (2023)
Shanshan Han, Wenxuan Wu, Baturalp Buyukates, Weizhao Jin, Yuhang Yao, Qifan Zhang, Salman Avestimehr, Chaoyang He
Kick Bad Guys Out! Zero-Knowledge-Proof-Based Anomaly Detection in Federated Learning. CoRR (2023)
Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr
The 1st International Workshop on Federated Learning with Graph Data (FedGraph). CIKM (2022)
Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, Amir Salman Avestimehr
Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities. IEEE Internet Things Mag. 5 (1) (2022)
Sunwoo Lee, Anit Kumar Sahu, Chaoyang He, Salman Avestimehr
Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits. CoRR (2022)
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 S. Silva R., Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. CoRR (2022)
Bill Yuchen Lin, Chaoyang He, Zihang Ze, Hulin Wang, Yufen Hua, Christophe Dupuy, Rahul Gupta, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks. NAACL-HLT (Findings) (2022)
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 Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. NeurIPS (2022)
Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data. AAAI (2022)
Chaoyang He, Shuai Zheng, Aston Zhang, George Karypis, Trishul Chilimbi, Mahdi Soltanolkotabi, Salman Avestimehr
SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing. CoRR (2022)
Chaoyang He, Alay Dilipbhai Shah, Zhenheng Tang, Di Fan, Adarshan Naiynar Sivashunmugam, Keerti Bhogaraju, Mita Shimpi, Li Shen, Xiaowen Chu, Mahdi Soltanolkotabi, Salman Avestimehr
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks. CoRR (2021)
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
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. NeurIPS (2021)
Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram, Salman Avestimehr
SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks. CoRR (2021)
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
A Field Guide to Federated Optimization. CoRR (2021)
Han Huang, Li Shen, Chaoyang He, Weisheng Dong, Haozhi Huang, Guangming Shi
Lightweight Image Super-Resolution with Hierarchical and Differentiable Neural Architecture Search. CoRR (2021)
Chaoyang He, Zhengyu Yang, Erum Mushtaq, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision. CoRR (2021)
Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen
AutoCTS: Automated Correlated Time Series Forecasting. Proc. VLDB Endow. 15 (4) (2021)
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models. ICML (2021)
Bill Yuchen Lin, Chaoyang He, Zihang Zeng, Hulin Wang, Yufen Huang, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr
FedNLP: A Research Platform for Federated Learning in Natural Language Processing. CoRR (2021)
Sunwoo Lee, Tuo Zhang, Chaoyang He, Salman Avestimehr
Layer-wise Adaptive Model Aggregation for Scalable Federated Learning. CoRR (2021)
Chien-Sheng Yang, Jinhyun So, Chaoyang He, Songze Li, Qian Yu, Salman Avestimehr
LightSecAgg: Rethinking Secure Aggregation in Federated Learning. CoRR (2021)
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers. CoRR (2021)
Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks. CoRR (2021)
Yahya H. Ezzeldin, Shen Yan, Chaoyang He, Emilio Ferrara, Salman Avestimehr
FairFed: Enabling Group Fairness in Federated Learning. CoRR (2021)
Tuo Zhang, Chaoyang He, Tianhao Ma, Mark Ma, Salman Avestimehr
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection. CoRR (2021)
Tuo Zhang, Chaoyang He, Tianhao Ma, Lei Gao, Mark Ma, Salman Avestimehr
Federated Learning for Internet of Things. SenSys (2021)
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
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge. CoRR (2021)
Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr
SPIDER: Searching Personalized Neural Architecture for Federated Learning. CoRR (2021)
Xinle Wu, Dalin Zhang, Chenjuan Guo, Chaoyang He, Bin Yang, Christian S. Jensen
AutoCTS: Automated Correlated Time Series Forecasting - Extended Version. CoRR (2021)
Tuo Zhang, Lei Gao, Chaoyang He, Mi Zhang, Bhaskar Krishnamachari, Salman Avestimehr
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities. CoRR (2021)
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
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14 (1-2) (2021)
Chaoyang He, Murali Annavaram, Salman Avestimehr
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge. NeurIPS (2020)
Chaoyang He, Murali Annavaram, Salman Avestimehr
FedNAS: Federated Deep Learning via Neural Architecture Search. CoRR (2020)
Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CVPR (2020)
Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr
FedML: A Research Library and Benchmark for Federated Machine Learning. CoRR (2020)
Chaoyang He, Haishan Ye, Li Shen, Tong Zhang
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. CoRR (2020)
Chaoyang He, Murali Annavaram, Salman Avestimehr
Group Knowledge Transfer: Collaborative Training of Large CNNs on the Edge. CoRR (2020)
Chrysovalantis Anastasiou, Jianfa Lin, Chaoyang He, Yao-Yi Chiang, Cyrus Shahabi
ADMSv2: A Modern Architecture for Transportation Data Management and Analysis. ARIC@SIGSPATIAL (2019)
Chaoyang He, Tian Xie, Yu Rong, Wen-bing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi
Adversarial Representation Learning on Large-Scale Bipartite Graphs. CoRR (2019)
Chaoyang He, Ming Li
Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps. CoRR (2019)
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, 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, 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
Advances and Open Problems in Federated Learning. CoRR (2019)
Zi Long, Lianzhi Tan, Shengping Zhou, Chaoyang He, Xin Liu
Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling. IJCNN (2019)
Chaoyang He, Conghui Tan, Hanlin Tang, Shuang Qiu, Ji Liu
Central Server Free Federated Learning over Single-sided Trust Social Networks. CoRR (2019)