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IEEE Transactions on Pattern Analysis and Machine Intelligence
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March 3, 2025
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
Zhenyi Wang, Enneng Yang, Li Shen, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
February 11, 2026
Exploring and Tailoring the Test-Time Augmentation for Sequential Recommendation
Yizhou Dang, Enneng Yang, Yuting Liu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
March 3, 2025
Revisiting Flatness-Aware Optimization in Continual Learning With Orthogonal Gradient Projection
Enneng Yang, Li Shen, Zhenyi Wang, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
September 20, 2024
Continual Learning From a Stream of APIs
Enneng Yang, Zhenyi Wang, Li Shen, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
November 6, 2025
Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging
Li Shen, Anke Tang, Enneng Yang, et al.
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of 1
Search research articles
Search
Showing results (1-10 of 5) with videos related to
Sort By:
Page
of 1
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
March 3, 2025
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
Zhenyi Wang, Enneng Yang, Li Shen, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
February 11, 2026
Exploring and Tailoring the Test-Time Augmentation for Sequential Recommendation
Yizhou Dang, Enneng Yang, Yuting Liu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
March 3, 2025
Revisiting Flatness-Aware Optimization in Continual Learning With Orthogonal Gradient Projection
Enneng Yang, Li Shen, Zhenyi Wang, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
September 20, 2024
Continual Learning From a Stream of APIs
Enneng Yang, Zhenyi Wang, Li Shen, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
|
November 6, 2025
Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging
Li Shen, Anke Tang, Enneng Yang, et al.
Page
of 1