| CHEX: CHannel EXploration for CNN Model Compression Z Hou, M Qin, F Sun, X Ma, K Yuan, Y Xu, YK Chen, R Jin, Y Xie, SY Kung IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 12287 …, 2022 | 51 | 2022 |
| MILAN: Masked Image Pretraining on Language Assisted Representation Z Hou, F Sun, YK Chen, Y Xie, SY Kung arXiv preprint arXiv:2208.06049, 2022 | 46 | 2022 |
| Effective model sparsification by scheduled grow-and-prune methods X Ma, M Qin, F Sun, Z Hou, K Yuan, Y Xu, Y Wang, YK Chen, R Jin, Y Xie International Conference on Learning Representations (ICLR), 2022 | 30 | 2022 |
| Efficient image super resolution via channel discriminative deep neural network pruning Z Hou, SY Kung International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2020 | 30 | 2020 |
| Multi-dimensional model compression of vision transformer Z Hou, SY Kung 2022 IEEE International Conference on Multimedia and Expo (ICME), 01-06, 2022 | 15 | 2022 |
| Multi-Dimensional Vision Transformer Compression via Dependency Guided Gaussian Process Search Z Hou, SY Kung IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 3669-3678, 2022 | 14 | 2022 |
| Meta-Learning the Difference: Preparing Large Language Models for Efficient Adaptation Z Hou, J Salazar, G Polovets Transactions of the Association for Computational Linguistics (TACL), 2022 | 9 | 2022 |
| A feature-map discriminant perspective for pruning deep neural networks Z Hou, SY Kung arXiv preprint arXiv:2005.13796, 2020 | 9 | 2020 |
| Multi-dimensional dynamic model compression for efficient image super-resolution Z Hou, SY Kung IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 633-643, 2022 | 7 | 2022 |
| Methodical design and trimming of deep learning networks: Enhancing external bp learning with internal omnipresent-supervision training paradigm SY Kung, Z Hou, Y Liu International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2019 | 7 | 2019 |
| A discriminant information approach to deep neural network pruning Z Hou, SY Kung International Conference on Pattern Recognition (ICPR), 9553-9560, 2021 | 6 | 2021 |
| Meta-learning with attention for improved few-shot learning Z Hou, A Walid, SY Kung International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2021 | 4 | 2021 |
| Parameter Efficient Dynamic Convolution via Tensor Decomposition Z Hou, SY Kung British Machine Vision Conference (BMVC), 2021 | 4 | 2021 |
| Augment deep BP-parameter learning with local XAI-structural learning SY Kung, Z Hou Communications in Information and Systems 20 (3), 319-352, 2020 | 4 | 2020 |
| A Kernel Discriminant Information Approach to Non-linear Feature Selection Z Hou, SY Kung International Joint Conference on Neural Networks (IJCNN), 1-10, 2019 | 3 | 2019 |
| Distributed optimal power flow: An Augmented Lagrangian-Sequential Quadratic Programming approach Z Hou, HC Wu, SC Chan IEEE International Symposium on Circuits and Systems (ISCAS), 1-4, 2017 | 3 | 2017 |
| Scalable kernel learning via the discriminant information M Al, Z Hou, SY Kung International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2020 | 2 | 2020 |
| Semi-supervised few-shot learning via dependency maximization and instance discriminant analysis Z Hou, SY Kung Journal of Signal Processing Systems 95 (1), 13-24, 2023 | 1 | 2023 |
| Model and Data Efficiency in Deep Learning Z Hou Princeton University, 2022 | 1 | 2022 |
| Semi-Supervised Few-Shot Learning From a Dependency-Discriminant Perspective Z Hou, SY Kung IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2817-2825, 2022 | 1 | 2022 |
Sun-Yuan KungProfessor of Electrical Engineering, Princeton UniversityVerified email at princeton.edu
