Da-Wei Zhou

Orcid: 0000-0001-7226-7773

Affiliations:
  • Nanjing University, Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, China


According to our database1, Da-Wei Zhou authored at least 26 papers between 2019 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Contextualizing Meta-Learning via Learning to Decompose.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2024

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning.
CoRR, 2024

Continual Learning with Pre-Trained Models: A Survey.
CoRR, 2024

2023
Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.
IEEE Trans. Pattern Anal. Mach. Intell., November, 2023

PyCIL: a Python toolbox for class-incremental learning.
Sci. China Inf. Sci., September, 2023

Cost-Effective Incremental Deep Model: Matching Model Capacity With the Least Sampling.
IEEE Trans. Knowl. Data Eng., April, 2023

RF-Badge: Vital Sign-Based Authentication via RFID Tag Array on Badges.
IEEE Trans. Mob. Comput., 2023

PILOT: A Pre-Trained Model-Based Continual Learning Toolbox.
CoRR, 2023

Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data.
CoRR, 2023

Learning without Forgetting for Vision-Language Models.
CoRR, 2023

Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need.
CoRR, 2023

Deep Class-Incremental Learning: A Survey.
CoRR, 2023

Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Preserving Locality in Vision Transformers for Class Incremental Learning.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

BEEF: Bi-Compatible Class-Incremental Learning via Energy-Based Expansion and Fusion.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Learning to Classify With Incremental New Class.
IEEE Trans. Neural Networks Learn. Syst., 2022

Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks.
CoRR, 2022

Audio-Visual Generalized Few-Shot Learning with Prototype-Based Co-Adaptation.
Proceedings of the Interspeech 2022, 2022

FOSTER: Feature Boosting and Compression for Class-Incremental Learning.
Proceedings of the Computer Vision - ECCV 2022, 2022

Forward Compatible Few-Shot Class-Incremental Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Contextualizing Multiple Tasks via Learning to Decompose.
CoRR, 2021

Detecting Sequentially Novel Classes with Stable Generalization Ability.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Co-Transport for Class-Incremental Learning.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Learning Placeholders for Open-Set Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2019
Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019


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