| POPQORN: Quantifying robustness of recurrent neural networks CY Ko, Z Lyu, L Weng, L Daniel, N Wong, D Lin International Conference on Machine Learning, 3468-3477, 2019 | 108 | 2019 |
| Fast and accurate tensor completion with total variation regularized tensor trains CY Ko, K Batselier, L Daniel, W Yu, N Wong IEEE Transactions on Image Processing 29, 6918-6931, 2020 | 59* | 2020 |
| Fastened crown: Tightened neural network robustness certificates Z Lyu, CY Ko, Z Kong, N Wong, D Lin, L Daniel Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5037-5044, 2020 | 55 | 2020 |
| Higher-order certification for randomized smoothing J Mohapatra, CY Ko, TW Weng, PY Chen, S Liu, L Daniel Advances in Neural Information Processing Systems 33, 4501-4511, 2020 | 36 | 2020 |
| Hidden cost of randomized smoothing J Mohapatra, CY Ko, L Weng, PY Chen, S Liu, L Daniel International Conference on Artificial Intelligence and Statistics, 4033-4041, 2021 | 31* | 2021 |
| A support tensor train machine C Chen, K Batselier, CY Ko, N Wong 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 24 | 2019 |
| Tensor network subspace identification of polynomial state space models K Batselier, CY Ko, N Wong Automatica 95, 187-196, 2018 | 20 | 2018 |
| Revisiting contrastive learning through the lens of neighborhood component analysis: an integrated framework CY Ko, J Mohapatra, S Liu, PY Chen, L Daniel, L Weng International Conference on Machine Learning, 11387-11412, 2022 | 12 | 2022 |
| Deep model compression and inference speedup of sum–product networks on tensor trains CY Ko, C Chen, Z He, Y Zhang, K Batselier, N Wong IEEE transactions on neural networks and learning systems 31 (7), 2665-2671, 2019 | 7* | 2019 |
| Visual pre-training for navigation: What can we learn from noise? Y Wang, CY Ko, P Agrawal 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 4 | 2023 |
| Misc: Mixed strategies crowdsourcing CY Ko, R Lin, S Li, N Wong Proceedings of the 28th International Joint Conference on Artificial …, 2019 | 4 | 2019 |
| Multilinear state space system identification with matrix product operators K Batselier, CY Ko, AH Phan, A Cichocki, N Wong IFAC-PapersOnLine 51 (15), 640-645, 2018 | 4 | 2018 |
| Synbench: Task-agnostic benchmarking of pretrained representations using synthetic data CY Ko, PY Chen, J Mohapatra, P Das, L Daniel arXiv preprint arXiv:2210.02989, 2022 | 3 | 2022 |
| Extended Kalman filtering with low-rank tensor networks for MIMO volterra system identification K Batselier, CY Ko, N Wong 2019 IEEE 58th Conference on Decision and Control (CDC), 7148-7153, 2019 | 3 | 2019 |
| Matrix product operator restricted Boltzmann machines C Chen, K Batselier, CY Ko, N Wong 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 3 | 2019 |
| On robustness-accuracy characterization of large language models using synthetic datasets CY Ko, PY Chen, P Das, YS Chuang, L Daniel Workshop on Efficient Systems for Foundation Models@ ICML2023, 2023 | 2 | 2023 |
| Sample-Specific Debiasing for Better Image-Text Models P Wang, Y Liu, CY Ko, WM Wells, S Berkowitz, S Horng, P Golland Machine Learning for Healthcare Conference, 788-803, 2023 | | 2023 |
| SynBench: Evaluating Pretrained Representations for Image Classification using Synthetic Data CY Ko, PY Chen, P Das, J Mohapatra, L Daniel | | 2023 |
| Facile Prediction of Neutrophil Activation State from Microscopy Images: A New Dataset and Comparative Deep Learning Approaches W Liao, CY Ko, TW Weng, L Daniel, J Voldman 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 1-5, 2022 | | 2022 |
| Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis CY Ko Massachusetts Institute of Technology, 2022 | | 2022 |
Ngai WongAssociate Professor of Electrical and Electronic Engineering, The University of Hong KongEmail verificata su eee.hku.hk
