受强制性开放获取政策约束的文章 - Ting-Wu Chin了解详情
可在其他位置公开访问的文章：11 篇
Towards Efficient Model Compression via Learned Global Ranking
TW Chin, R Ding, C Zhang, D Marculescu
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2020
强制性开放获取政策： US National Science Foundation
Regularizing activation distribution for training binarized deep networks
R Ding, TW Chin, Z Liu, D Marculescu
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
强制性开放获取政策： US National Science Foundation
Adascale: Towards real-time video object detection using adaptive scaling
TW Chin, R Ding, D Marculescu
MLSys 2019: The Conference on Machine Learning and Systems, 2019
强制性开放获取政策： US National Science Foundation
Designing Adaptive Neural Networks for Energy-Constrained Image Classification
D Stamoulis, TW Chin, AK Prakash, H Fang, S Sajja, M Bognar, ...
Proceedings of the International Conference on Computer-Aided Design, 2018
强制性开放获取政策： US National Science Foundation
Flightnns: Lightweight quantized deep neural networks for fast and accurate inference
R Ding, Z Liu, TW Chin, D Marculescu, RD Blanton
Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019
强制性开放获取政策： US National Science Foundation
One Weight Bitwidth to Rule Them All
TW Chin, PIJ Chuang, V Chandra, D Marculescu
ECCV Workshops (Best paper in Embedded Vision Workshop), 2020
强制性开放获取政策： US National Science Foundation
Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks
TW Chin, AS Morcos, D Marculescu
ECML-PKDD (Research Track), 2021
强制性开放获取政策： US National Science Foundation
Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness
TW Chin, C Zhang, D Marculescu
CVPR Workshops (Best paper in Fair, Data Efficient and Trusted Computer Vision), 2021
强制性开放获取政策： US National Science Foundation
QUIDAM: A Framework for Quantization-aware DNN Accelerator and Model Co-Exploration
A Inci, S Virupaksha, A Jain, TW Chin, V Thallam, R Ding, D Marculescu
ACM Transactions on Embedded Computing Systems 22 (2), 1-21, 2023
强制性开放获取政策： US National Science Foundation
Width Transfer: On the (In) variance of Width Optimization
TW Chin, D Marculescu, AS Morcos
CVPR Workshops (Efficient Deep Learning for Computer Vision), 2021
强制性开放获取政策： US National Science Foundation
Ant: Adapt network across time for efficient video processing
F Liang, TW Chin, Y Zhou, D Marculescu
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
强制性开放获取政策： US National Science Foundation
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