Chuan-Sheng Foo

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 66

Top Topics

Active Learning

Domain Adaptation

Anomaly Detection

Top Venues

IEEE Trans. Image Process.

Trans. Mach. Learn. Res.

Publications

Weide Liu, Zhonghua Wu, Yang Zhao, Yuming Fang, Chuan-Sheng Foo, Jun Cheng, Guosheng Lin
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation. Int. J. Comput. Vis. 132 (4) (2024)
Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions. CoRR (2024)
Wenyu Zhang, Qingmu Liu, Felix Ong Wei Cong, Mohamed Ragab, Chuan-Sheng Foo
Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias. CoRR (2024)
Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low
A Unified Framework for Bayesian Optimization under Contextual Uncertainty. ICLR (2024)
Mohamed Ragab, Peiliang Gong, Emadeldeen Eldele, Wenyu Zhang, Min Wu, Chuan-Sheng Foo, Daoqiang Zhang, Xiaoli Li, Zhenghua Chen
Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation. CoRR (2024)
Yiting Li, Adam David Goodge, Fayao Liu, Chuan-Sheng Foo
PromptAD: Zero-shot Anomaly Detection using Text Prompts. WACV (2024)
Wenyu Zhang, Fayao Liu, Cuong Manh Nguyen, Zhong Liang Ou Yang, Savitha Ramasamy, Chuan-Sheng Foo
Training neural networks with classification rules for incorporating domain knowledge. Knowl. Based Syst. 294 (2024)
Yinan He, Lile Cai, Jingyi Liao, Chuan-Sheng Foo
Hybrid Active Learning with Uncertainty-Weighted Embeddings. Trans. Mach. Learn. Res. 2024 (2024)
Gregory Kang Ruey Lau, Xinyuan Niu, Hieu Dao, Jiangwei Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
Waterfall: Framework for Robust and Scalable Text Watermarking. CoRR (2024)
Brian Formento, Wenjie Feng, Chuan-Sheng Foo, Anh Tuan Luu, See-Kiong Ng
SemRoDe: Macro Adversarial Training to Learn Representations that are Robust to Word-Level Attacks. NAACL-HLT (2024)
Cheng Chen, Xiaofeng Yang, Fan Yang, Chengzeng Feng, Zhoujie Fu, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu
Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior. CoRR (2024)
Chaoyue Song, Jiacheng Wei, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu
REACTO: Reconstructing Articulated Objects from a Single Video. CoRR (2024)
Wenyu Zhang, Li Shen, Chuan-Sheng Foo
Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-Training. CoRR (2024)
Brian Formento, Chuan-Sheng Foo, Anh Tuan Luu, See-Kiong Ng
Using Punctuation as an Adversarial Attack on Deep Learning-Based NLP Systems: An Empirical Study. EACL (Findings) (2023)
Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen
Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. KDD (2023)
Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo
PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation. CoRR (2023)
Cuong Manh Nguyen, Arun Raja, Le Zhang, Xun Xu, Balagopal Unnikrishnan, Mohamed Ragab, Kangkang Lu, Chuan-Sheng Foo
Diverse and consistent multi-view networks for semi-supervised regression. Mach. Learn. 112 (7) (2023)
Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low
Fair yet Asymptotically Equal Collaborative Learning. CoRR (2023)
Wenyu Zhang, Li Shen, Chuan-Sheng Foo
Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation. ICCV (2023)
Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen
Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. CoRR (2023)
Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low
Fair yet Asymptotically Equal Collaborative Learning. ICML (2023)
Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo
Mitigating Real-World Distribution Shifts in the Fourier Domain. Trans. Mach. Learn. Res. 2023 (2023)
Weide Liu, Zhonghua Wu, Yang Zhao, Yuming Fang, Chuan-Sheng Foo, Jun Cheng, Guosheng Lin
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation. CoRR (2023)
Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo
Fourier Sensitivity and Regularization of Computer Vision Models. CoRR (2023)
Jingtan Wang, Xinyang Lu, Zitong Zhao, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low
WASA: WAtermark-based Source Attribution for Large Language Model-Generated Data. CoRR (2023)
Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. ACM Trans. Knowl. Discov. Data 17 (8) (2023)
Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi
Classify and generate: Using classification latent space representations for image generations. Neurocomputing 471 (2022)
Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. CoRR (2022)
Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo
Few-Shot Adaptation of Pre-Trained Networks for Domain Shift. CoRR (2022)
Astha Garg, Wenyu Zhang, Jules Samaran, Ramasamy Savitha, Chuan-Sheng Foo
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series. IEEE Trans. Neural Networks Learn. Syst. 33 (6) (2022)
Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo
Few-Shot Adaptation of Pre-Trained Networks for Domain Shift. IJCAI (2022)
Wenyu Zhang, Li Shen, Chuan-Sheng Foo
Co-Learning with Pre-Trained Networks Improves Source-Free Domain Adaptation. CoRR (2022)
Lile Cai, Ramanpreet Singh Pahwa, Xun Xu, Jie Wang, Richard Chang, Lining Zhang, Chuan-Sheng Foo
Exploring Active Learning for Semiconductor Defect Segmentation. ICIP (2022)
Fayao Liu, Guosheng Lin, Chuan-Sheng Foo, Chaitanya K. Joshi, Jie Lin
Point Discriminative Learning for Data-efficient 3D Point Cloud Analysis. 3DV (2022)
Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota
Scalable and Practical Natural Gradient for Large-Scale Deep Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44 (1) (2022)
Wenyu Zhang, Mohamed Ragab, Chuan-Sheng Foo
Domain Generalization via Selective Consistency Regularization for Time Series Classification. ICPR (2022)
Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo
Fourier Sensitivity and Regularization of Computer Vision Models. Trans. Mach. Learn. Res. 2022 (2022)
Xun Xu, Cuong Manh Nguyen, Yasin Yazici, Kangkang Lu, Hlaing Min, Chuan-Sheng Foo
SemiCurv: Semi-Supervised Curvilinear Structure Segmentation. IEEE Trans. Image Process. 31 (2022)
Manas Gupta, Efe Camci, Vishandi Rudy Keneta, Abhishek Vaidyanathan, Ritwik Kanodia, Chuan-Sheng Foo, Min Wu, Jie Lin
Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning. CoRR (2022)
Xun Xu, Manh Cuong Nguyen, Yasin Yazici, Kangkang Lu, Hlaing Min, Chuan-Sheng Foo
SemiCurv: Semi-Supervised Curvilinear Structure Segmentation. CoRR (2022)
Wenyu Zhang, Mohamed Ragab, Chuan-Sheng Foo
Domain Generalization via Selective Consistency Regularization for Time Series Classification. CoRR (2022)
Yasin Yazici, Bruno Lecouat, Kim-Hui Yap, Stefan Winkler, Georgios Piliouras, Vijay Chandrasekhar, Chuan-Sheng Foo
Mixed Membership Generative Adversarial Networks. ICIP (2022)
Wanyue Zhang, Xun Xu, Fayao Liu, Le Zhang, Chuan-Sheng Foo
On Automatic Data Augmentation for 3D Point Cloud Classification. CoRR (2021)
Lile Cai, Xun Xu, Lining Zhang, Chuan-Sheng Foo
Exploring Spatial Diversity for Region-Based Active Learning. IEEE Trans. Image Process. 30 (2021)
Astha Garg, Wenyu Zhang, Jules Samaran, Savitha Ramasamy, Chuan-Sheng Foo
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series. CoRR (2021)
Kangkang Lu, Cuong Manh Nguyen, Xun Xu, Kiran Chari, Yu Jing Goh, Chuan-Sheng Foo
ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity. ICLR (2021)
Brian Formento, See-Kiong Ng, Chuan-Sheng Foo
Special Symbol Attacks On NLP Systems. IJCNN (2021)
Fayao Liu, Guosheng Lin, Chuan-Sheng Foo
Point Discriminative Learning for Unsupervised Representation Learning on 3D Point Clouds. CoRR (2021)
Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan-Sheng Foo
On Representation Knowledge Distillation for Graph Neural Networks. CoRR (2021)
Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar
Empirical Analysis of Overfitting and Mode Drop in GAN Training. CoRR (2020)
Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar
Empirical Analysis Of Overfitting And Mode Drop In Gan Training. ICIP (2020)
Yubo Hou, Zhenghua Chen, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Raed M. Shubair
Mahalanobis Distance Based Adversarial Network for Anomaly Detection. ICASSP (2020)
Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota
Scalable and Practical Natural Gradient for Large-Scale Deep Learning. CoRR (2020)
Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar
Holistic Multi-Modal Memory Network for Movie Question Answering. IEEE Trans. Image Process. 29 (2020)
Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi
Classification Representations Can be Reused for Downstream Generations. CoRR (2020)
Yasin Yazici, Bruno Lecouat, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar
Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions. CoRR (2019)
Khalil Ouardini, Huijuan Yang, Balagopal Unnikrishnan, Manon Romain, Camille Garcin, Houssam Zenati, J. Peter Campbell, Michael F. Chiang, Jayashree Kalpathy-Cramer, Vijay Chandrasekhar, Pavitra Krishnaswamy, Chuan-Sheng Foo
Towards Practical Unsupervised Anomaly Detection on Retinal Images. DART/MIL3ID@MICCAI (2019)
Kangkang Lu, Chuan-Sheng Foo, Kah Kuan Teh, Huy Dat Tran, Vijay Ramaseshan Chandrasekhar
Semi-Supervised Audio Classification with Consistency-Based Regularization. INTERSPEECH (2019)
Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile. ICLR (Poster) (2019)
Wei-Hong Li, Chuan-Sheng Foo, Hakan Bilen
Learning to Impute: A General Framework for Semi-supervised Learning. CoRR (2019)
Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar
The Unusual Effectiveness of Averaging in GAN Training. ICLR (Poster) (2019)
Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar
Adversarially Learned Anomaly Detection. ICDM (2018)
Leo Laugier, Daniil Bash, Jose Recatala, Hong Kuan Ng, Savitha Ramasamy, Chuan-Sheng Foo, Vijay Ramaseshan Chandrasekhar, Kedar Hippalgaonkar
Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials. CoRR (2018)
Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. CoRR (2018)
Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras
Mirror descent in saddle-point problems: Going the extra (gradient) mile. CoRR (2018)
Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar
Holistic Multi-modal Memory Network for Movie Question Answering. CoRR (2018)
Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
A majorization-minimization algorithm for (multiple) hyperparameter learning. ICML (2009)
Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
Proximal regularization for online and batch learning. ICML (2009)
Chuong B. Do, Chuan-Sheng Foo, Serafim Batzoglou
A max-margin model for efficient simultaneous alignment and folding of RNA sequences. ISMB (2008)
Chuong B. Do, Chuan-Sheng Foo, Andrew Y. Ng
Efficient multiple hyperparameter learning for log-linear models. NIPS (2007)