Jiaxiang Ren

Affiliations:
  • Auburn University, Auburn, AL, USA


According to our database1, Jiaxiang Ren authored at least 12 papers between 2019 and 2024.

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

Timeline

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Bibliography

2024
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-aware Model Update.
CoRR, 2023

Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing.
Proceedings of the International Conference on Machine Learning, 2023

Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022
Unsupervised Adversarial Network Alignment with Reinforcement Learning.
ACM Trans. Knowl. Discov. Data, 2022

Accelerated Federated Learning with Decoupled Adaptive Optimization.
Proceedings of the International Conference on Machine Learning, 2022

2021
Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Integrated Defense for Resilient Graph Matching.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Robust Meta Network Embedding against Adversarial Attacks.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Unsupervised Multiple Network Alignment with Multinominal GAN and Variational Inference.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Dual Adversarial Learning Based Network Alignment.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Semi-supervised Classification-based Local Vertex Ranking via Dual Generative Adversarial Nets.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019


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