Chaoyang He

Xiangyu Chang

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Partial model averaging in Federated Learning: Performance guarantees and benefits.

[BibT_eX]

[DOI]

Neurocomputing, November, 2023

Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution.

[BibT_eX]

[DOI]

IEEE Trans. Circuits Syst. Video Technol., June, 2023

Achieving small-batch accuracy with large-batch scalability via Hessian-aware learning rate adjustment.

[BibT_eX]

[DOI]

Sunwoo Lee

Neural Networks, January, 2023

Kick Bad Guys Out! Zero-Knowledge-Proof-Based Anomaly Detection in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Privacy-Preserving Federated Heavy Hitter Analytics for Non-IID Data.

[BibT_eX]

[DOI]

CoRR, 2023

Don't Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory.

[BibT_eX]

[DOI]

CoRR, 2023

FedMLSecurity: A Benchmark for Attacks and Defenses in Federated Learning and LLMs.

[BibT_eX]

[DOI]

CoRR, 2023

FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System.

[BibT_eX]

[DOI]

CoRR, 2023

FedML Parrot: A Scalable Federated Learning System via Heterogeneity-aware Scheduling on Sequential and Hierarchical Training.

[BibT_eX]

[DOI]

CoRR, 2023

Federated Analytics: A survey.

[BibT_eX]

[DOI]

Ahmed Roushdy Elkordy

CoRR, 2023

A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Proof-of-Contribution-Based Design for Collaborative Machine Learning on Blockchain.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Decentralized Applications and Infrastructures, 2023

FairFed: Enabling Group Fairness in Federated Learning.

[BibT_eX]

[DOI]

Amir Salman Avestimehr

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Federated Learning for the Internet of Things: Applications, Challenges, and Opportunities.

[BibT_eX]

[DOI]

Bhaskar Krishnamachari

Amir Salman Avestimehr

IEEE Internet Things Mag., 2022

SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing.

[BibT_eX]

[DOI]

CoRR, 2022

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

The 1st International Workshop on Federated Learning with Graph Data (FedGraph).

[BibT_eX]

[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data.

[BibT_eX]

[DOI]

Emir Ceyani

Keshav Balasubramanian

Adarshan Naiynar Sivashunmugam

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

AutoCTS: Automated Correlated Time Series Forecasting.

[BibT_eX]

[DOI]

Proc. VLDB Endow., 2021

Advances and Open Problems in Federated Learning.

[BibT_eX]

[DOI]

Rafael G. L. D'Oliveira

Ananda Theertha Suresh

Found. Trends Mach. Learn., 2021

SPIDER: Searching Personalized Neural Architecture for Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2021

AutoCTS: Automated Correlated Time Series Forecasting - Extended Version.

[BibT_eX]

[DOI]

CoRR, 2021

FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks.

[BibT_eX]

[DOI]

CoRR, 2021

Layer-wise Adaptive Model Aggregation for Scalable Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2021

SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision.

[BibT_eX]

[DOI]

CoRR, 2021

LightSecAgg: Rethinking Secure Aggregation in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2021

A Field Guide to Federated Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection.

[BibT_eX]

[DOI]

CoRR, 2021

SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks.

[BibT_eX]

[DOI]

Emir Ceyani

Keshav Balasubramanian

CoRR, 2021

Lightweight Image Super-Resolution with Hierarchical and Differentiable Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2021

FedNLP: A Research Platform for Federated Learning in Natural Language Processing.

[BibT_eX]

[DOI]

CoRR, 2021

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks.

[BibT_eX]

[DOI]

Keshav Balasubramanian

CoRR, 2021

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Transformers.

[BibT_eX]

[DOI]

CoRR, 2021

Federated Learning for Internet of Things.

[BibT_eX]

[DOI]

Proceedings of the SenSys '21: The 19th ACM Conference on Embedded Networked Sensor Systems, Coimbra, Portugal, November 15, 2021

MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Group Knowledge Transfer: Collaborative Training of Large CNNs on the Edge.

[BibT_eX]

[DOI]

CoRR, 2020

FedML: A Research Library and Benchmark for Federated Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2020

FedNAS: Federated Deep Learning via Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2020

Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Advances and Open Problems in Federated Learning.

[BibT_eX]

[DOI]

Rafael G. L. D'Oliveira

Ananda Theertha Suresh

CoRR, 2019

Central Server Free Federated Learning over Single-sided Trust Social Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Efficient Spatial Anti-Aliasing Rendering for Line Joins on Vector Maps.

[BibT_eX]

[DOI]