Ting-Wu Chin

According to our database, Ting-Wu Chin authored at least 22 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

QUIDAM: A Framework for Quantization-aware DNN Accelerator and Model Co-Exploration.

Ahmet Inci, Siri Garudanagiri Virupaksha, Aman Jain, Ting-Wu Chin, Venkata Vivek Thallam, Ruizhou Ding, Diana Marculescu

ACM Trans. Embed. Comput. Syst., March, 2023

2022

On Designing Resource-Constrained CNNs Efficiently.

Ting-Wu Chin

PhD thesis, 2022

Play It Cool: Dynamic Shifting Prevents Thermal Throttling.

Yang Zhou, Feng Liang, Ting-Wu Chin, Diana Marculescu

CoRR, 2022

ANT: Adapt Network Across Time for Efficient Video Processing.

Feng Liang, Ting-Wu Chin, Yang Zhou, Diana Marculescu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021

Putting the "Machine" Back in Machine Learning for Engineering Students.

Ting-Wu Chin, Dimitrios Stamoulis, Diana Marculescu

Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, 2021

Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks.

Ting-Wu Chin, Ari S. Morcos, Diana Marculescu

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Renofeation: A Simple Transfer Learning Method for Improved Adversarial Robustness.

Ting-Wu Chin, Cha Zhang, Diana Marculescu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Width Transfer: On the (In)variance of Width Optimization.

Ting-Wu Chin, Diana Marculescu, Ari S. Morcos

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

PareCO: Pareto-aware Channel Optimization for Slimmable Neural Networks.

Ting-Wu Chin, Ari S. Morcos, Diana Marculescu

CoRR, 2020

Improving the Adversarial Robustness of Transfer Learning via Noisy Feature Distillation.

Ting-Wu Chin, Cha Zhang, Diana Marculescu

CoRR, 2020

One Weight Bitwidth to Rule Them All.

Ting-Wu Chin, Pierce I-Jen Chuang, Vikas Chandra, Diana Marculescu

Proceedings of the Computer Vision - ECCV 2020 Workshops, 2020

Towards Efficient Model Compression via Learned Global Ranking.

Ting-Wu Chin, Ruizhou Ding, Cha Zhang, Diana Marculescu

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

LeGR: Filter Pruning via Learned Global Ranking.

Ting-Wu Chin, Ruizhou Ding, Cha Zhang, Diana Marculescu

CoRR, 2019

AdaScale: Towards Real-time Video Object Detection using Adaptive Scaling.

Ting-Wu Chin, Ruizhou Ding, Diana Marculescu

Proceedings of Machine Learning and Systems 2019, 2019

FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference.

Ruizhou Ding, Zeye Liu, Ting-Wu Chin, Diana Marculescu, R. D. (Shawn) Blanton

Proceedings of the 56th Annual Design Automation Conference 2019, 2019

Regularizing Activation Distribution for Training Binarized Deep Networks.

Ruizhou Ding, Ting-Wu Chin, Zeye Liu, Diana Marculescu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Domain-Specific Approximation for Object Detection.

Ting-Wu Chin, Chia-Lin Yu, Matthew Halpern, Hasan Genc, Shiao-Li Tsao, Vijay Janapa Reddi

IEEE Micro, 2018

Layer-compensated Pruning for Resource-constrained Convolutional Neural Networks.

Ting-Wu Chin, Cha Zhang, Diana Marculescu

CoRR, 2018

Understanding the Impact of Label Granularity on CNN-Based Image Classification.

Zhuo Chen, Ruizhou Ding, Ting-Wu Chin, Diana Marculescu

Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

Designing adaptive neural networks for energy-constrained image classification.

Dimitrios Stamoulis, Ting-Wu (Rudy) Chin, Anand Krishnan Prakash, Haocheng Fang, Sribhuvan Sajja, Mitchell Bognar, Diana Marculescu

Proceedings of the International Conference on Computer-Aided Design, 2018

2017

Flying IoT: Toward Low-Power Vision in the Sky.

Hasan Genc, Yazhou Zu, Ting-Wu Chin, Matthew Halpern, Vijay Janapa Reddi

IEEE Micro, 2017

Improving the accuracy of the leakage power estimation of embedded CPUs.

Ting-Wu Chin, Shiao-Li Tsao, Kuo-Wei Hung, Pei-Shu Huang

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017