Efficient continual learning at the edge with progressive segmented training.
Neuromorph. Comput. Eng., December, 2022
Exploring Model Stability of Deep Neural Networks for Reliable RRAM-Based In-Memory Acceleration.
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IEEE Trans. Computers, 2022
Robust RRAM-based In-Memory Computing in Light of Model Stability.
Proceedings of the IEEE International Reliability Physics Symposium, 2021
Evolutionary NAS in Light of Model Stability for Accurate Continual Learning.
Proceedings of the International Joint Conference on Neural Networks, 2021
Visual Perception, Prediction and Understanding with Relations.
PhD thesis, 2020
GAR: Graph Assisted Reasoning for Object Detection.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020
Online Knowledge Acquisition with the Selective Inherited Model.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Efficient and Modularized Training on FPGA for Real-time Applications.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020
DAT-RNN: Trajectory Prediction with Diverse Attention.
Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020
Noise-based Selection of Robust Inherited Model for Accurate Continual Learning.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Efficient Network Construction Through Structural Plasticity.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2019
Towards Efficient Neural Networks On-a-chip: Joint Hardware-Algorithm Approaches.
CoRR, 2019
CGaP: Continuous Growth and Pruning for Efficient Deep Learning.
CoRR, 2019