Zexi Li

Orcid: 0000-0003-0831-3549

Affiliations:
  • Zhejiang University, College of Computer Science and Technology, Hangzhou, China


According to our database1, Zexi Li authored at least 16 papers between 2021 and 2024.

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

Timeline

Legend:

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Bibliography

2024
Improving Group Connectivity for Generalization of Federated Deep Learning.
CoRR, 2024

Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models.
CoRR, 2024

Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion.
CoRR, 2024

Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning.
CoRR, 2023

Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance.
CoRR, 2023

Universal Domain Adaptation via Compressive Attention Matching.
CoRR, 2023

Edge-cloud Collaborative Learning with Federated and Centralized Features.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Revisiting Weighted Aggregation in Federated Learning with Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

Universal Domain Adaptation via Compressive Attention Matching.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Can we share models if sharing data is not an option?
Patterns, 2022

Mining Latent Relationships among Clients: Peer-to-peer Federated Learning with Adaptive Neighbor Matching.
CoRR, 2022

2021
Ensemble Federated Adversarial Training with Non-IID data.
CoRR, 2021

Boosting the generalization ability of Vis-NIR-spectroscopy-based regression models through dimension reduction and transfer learning.
Comput. Electron. Agric., 2021


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