| 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 | 58 | 2019 |
| 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 | 56* | 2020 |
| 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 | 42 | 2018 |
| Layer-compensated pruning for resource-constrained convolutional neural networks TW Chin, C Zhang, D Marculescu NeurIPS 2018 Workshop MLPCD 2, 2018 | 36 | 2018 |
| 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 | 29 | 2019 |
| Flying IoT: Toward low-power vision in the sky H Genc, Y Zu, TW Chin, M Halpern, VJ Reddi IEEE Micro 37 (6), 40-51, 2017 | 27 | 2017 |
| Understanding the impact of label granularity on cnn-based image classification Z Chen, R Ding, TW Chin, D Marculescu 2018 IEEE international conference on data mining workshops (ICDMW), 895-904, 2018 | 18 | 2018 |
| 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 | 12 | 2019 |
| One Weight Bitwidth to Rule Them All TW Chin, PIJ Chuang, V Chandra, D Marculescu ECCV Workshops (Best paper in Embedded Vision Workshop), 2020 | 10 | 2020 |
| Domain-specific approximation for object detection TW Chin, CL Yu, M Halpern, H Genc, SL Tsao, VJ Reddi IEEE Micro 38 (1), 31-40, 2018 | 10 | 2018 |
| Joslim: Joint Widths and Weights Optimization for Slimmable Neural Networks TW Chin, AS Morcos, D Marculescu ECML-PKDD (Research Track), 2021 | 6* | 2021 |
| Optimizing sensor-cloud architectures for real-time autonomous drone operation H Genc, TW Chin, M Halpern, VJ Reddi Sensors to Cloud Architectures Workshop (SCAW), 2017 | 5 | 2017 |
| Width Transfer: On the (In) variance of Width Optimization TW Chin, D Marculescu, AS Morcos CVPR Workshops (Efficient Deep Learning for Computer Vision), 2021 | 3 | 2021 |
| 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 | 2* | 2021 |
| Improving the accuracy of the leakage power estimation of embedded CPUs TW Chin, SL Tsao, KW Hung, PS Huang Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 …, 2017 | 1 | 2017 |
| On Designing Resource-Constrained CNNs Efficiently TW Chin Carnegie Mellon University, 2021 | | 2021 |
| Flexible, lightweight quantized deep neural networks R Ding, Z Liu, TW Chin, D Marculescu, RD Blanton US Patent App. 16/887,988, 2020 | | 2020 |
| Differentiable Training for Hardware Efficient LightNNs R Ding, Z Liu, TW Chin, D Marculescu, RDS Blanton | | 2018 |
Diana MarculescuThe University of Texas at AustinVerified email at utexas.edu
