Gang Yan

Orcid: 0000-0002-7734-1589

Affiliations:
  • Jilin University, Changchun, China
  • University of California Merced, CA, USA (2024 - 2025)
  • Binghamton University, NY, USA (PhD 2023)


According to our database1, Gang Yan authored at least 15 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2025
FedDiAL: Adaptive Federated Learning with Hierarchical Discriminative Network for Large Pre-trained Models.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

FedSTEP: Asynchronous and Staleness-Aware Personalization for Efficient Federated Learning.
Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024
Enhancing Model Poisoning Attacks to Byzantine-Robust Federated Learning via Critical Learning Periods.
Proceedings of the 27th International Symposium on Research in Attacks, 2024

Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates.
Proceedings of the Twenty-fifth International Symposium on Theory, 2024

FedRoLA: Robust Federated Learning Against Model Poisoning via Layer-based Aggregation.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
CriticalFL: A Critical Learning Periods Augmented Client Selection Framework for Efficient Federated Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Towards Latency Awareness for Content Delivery Network Caching.
Proceedings of the 2022 USENIX Annual Technical Conference, 2022

Reinforcement Learning for Dynamic Dimensioning of Cloud Caches: A Restless Bandit Approach.
Proceedings of the IEEE INFOCOM 2022, 2022

Seizing Critical Learning Periods in Federated Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Critical Learning Periods in Federated Learning.
CoRR, 2021

Straggler-Resilient Distributed Machine Learning with Dynamic Backup Workers.
CoRR, 2021

Learning from optimal caching for content delivery.
Proceedings of the CoNEXT '21: The 17th International Conference on emerging Networking EXperiments and Technologies, Virtual Event, Munich, Germany, December 7, 2021

2020
RL-Bélády: A Unified Learning Framework for Content Caching.
Proceedings of the MM '20: The 28th ACM International Conference on Multimedia, 2020


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