Chuan Sheng Foo

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 46

Top Topics

Top Venues

IEEE Trans. Image Process.

Publications

Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin
Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction. CoRR (2024)
Jingyi Liao, Xun Xu, Manh Cuong Nguyen, Adam Goodge, Chuan Sheng Foo
COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection. CoRR (2024)
Xun Xu, Jingyi Liao, Lile Cai, Manh Cuong Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo
Revisiting pretraining for semi-supervised learning in the low-label regime. Neurocomputing 565 (2024)
Brian Formento, Wenjie Feng, Chuan Sheng Foo, Luu Anh Tuan, See-Kiong Ng
SemRoDe: Macro Adversarial Training to Learn Representations That are Robust to Word-Level Attacks. CoRR (2024)
Jingyi Liao, Xun Xu, Manh Cuong Nguyen, Adam Goodge, Chuan Sheng Foo
COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection. IEEE Trans. Image Process. 33 (2024)
Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan Sheng Foo
On Representation Knowledge Distillation for Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 35 (4) (2024)
Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin
Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction. AAAI (2024)
Sezin Kircali Ata, Zhi-Hui Kong, Anusha James, Lile Cai, Kiat Seng Yeo, Khin Mi Mi Aung, Chuan Sheng Foo, Ashish James
The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design. ISCAS (2024)
Chaoyue Song, Tianyi Chen, Yiwen Chen, Jiacheng Wei, Chuan Sheng Foo, Fayao Liu, Guosheng Lin
MoDA: Modeling Deformable 3D Objects from Casual Videos. CoRR (2023)
Sebastian Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low
Bayesian Optimization with Cost-varying Variable Subsets. NeurIPS (2023)
Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, Bryan Kian Hsiang Low
FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery. AISTATS (2023)
Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Bryan Kian Hsiang Low
Probably Approximate Shapley Fairness with Applications in Machine Learning. AAAI (2023)
Xinyi Xu, Thanh Lam, Chuan Sheng Foo, Bryan Kian Hsiang Low
Model Shapley: Equitable Model Valuation with Black-box Access. NeurIPS (2023)
Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low
No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities. AISTATS (2023)
Kangkang Lu, Manh Cuong Nguyen, Xun Xu, Chuan Sheng Foo
On Adversarial Robustness of Audio Classifiers. ICASSP (2023)
Lining Zhang, Salahuddin Raju, Ashish James, Rahul Dutta, Gregoire Fournier, Damien Lancry, Kevin Chai Tshun Chuan, Vijay Ramaseshan Chandrasekhar, Chuan Sheng Foo
Bayesian Deep Active Learning for Analog Circuit Performance Classification. ISCAS (2022)
Xian Shi, Xun Xu, Wanyue Zhang, Xiatian Zhu, Chuan Sheng Foo, Kui Jia
Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding. ICPR (2022)
Huijuan Yang, Aaron S. Coyner, Feri Guretno, Ivan Ho Mien, Chuan Sheng Foo, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, Pavitra Krishnaswamy
A Minimally Supervised Approach for Medical Image Quality Assessment in Domain Shift Settings. ICASSP (2022)
Rahul Dutta, Ashish James, Salahuddin Raju, Yong-Joon Jeon, Chuan Sheng Foo, Kevin Tshun Chuan Chai
Automated Deep Learning Platform for Accelerated Analog Circuit Design. SOCC (2022)
Xian Shi, Xun Xu, Wanyue Zhang, Xiatian Zhu, Chuan Sheng Foo, Kui Jia
Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding. CoRR (2022)
Xun Xu, Jingyi Liao, Lile Cai, Cuong Manh Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo
Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime. CoRR (2022)
Zeyu Jiang, Xun Xu, Le Zhang, Chao Zhang, Chuan Sheng Foo, Ce Zhu
MA-GANet: A Multi-Attention Generative Adversarial Network for Defocus Blur Detection. IEEE Trans. Image Process. 31 (2022)
Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Kian Hsiang Low
Probably Approximate Shapley Fairness with Applications in Machine Learning. CoRR (2022)
Sebastian Shenghong Tay, Chuan Sheng Foo, Urano Daisuke, Richalynn Leong, Bryan Kian Hsiang Low
Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity. ICML (2022)
Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low
Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards. AAAI (2022)
Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low
Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards. CoRR (2021)
Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low
Validation Free and Replication Robust Volume-based Data Valuation. NeurIPS (2021)
Mohamed Ragab, Zhenghua Chen, Min Wu, Chuan Sheng Foo, Chee Keong Kwoh, Ruqiang Yan, Xiaoli Li
Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction. IEEE Trans. Ind. Informatics 17 (8) (2021)
Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chao Li, Chuan Sheng Foo, Pavitra Krishnaswamy
Semi-supervised classification of radiology images with NoTeacher: A teacher that is not mean. Medical Image Anal. 73 (2021)
Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low
Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning. NeurIPS (2021)
Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chao Li, Chuan Sheng Foo, Pavitra Krishnaswamy
Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Mean. CoRR (2021)
Xian Shi, Xun Xu, Ke Chen, Lile Cai, Chuan Sheng Foo, Kui Jia
Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach. CoRR (2021)
Govind Narasimman, Kangkang Lu, Arun Raja, Chuan Sheng Foo, Mohamed M. Sabry Aly, Jie Lin, Vijay Chandrasekhar
A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity Recognition. CoRR (2021)
Wanyue Zhang, Xun Xu, Fayao Liu, Le Zhang, Chuan Sheng Foo
On Automatic Data Augmentation for 3D Point Cloud Classification. BMVC (2021)
Lile Cai, Xun Xu, Jun Hao Liew, Chuan Sheng Foo
Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs. CVPR (2021)
Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chuan Sheng Foo, Pavitra Krishnaswamy
Semi-supervised Classification of Diagnostic Radiographs with NoTeacher: A Teacher that is Not Mean. MICCAI (1) (2020)
Lile Cai, Bin Zhao, Zhe Wang, Jie Lin, Chuan Sheng Foo, Mohamed M. Sabry Aly, Vijay Chandrasekhar
MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors. CVPR (2019)
Rahul Dutta, Salahuddin Raju, Ashish James, Leo John Chemmanda, Yong-Joon Jeon, Balagopal Unnikrishnan, Chuan Sheng Foo, Zeng Zeng, Kevin Tshun Chuan Chai, Vijay Ramaseshan Chandrasekhar
Learning of Multi-Dimensional Analog Circuits Through Generative Adversarial Network (GAN). SoCC (2019)
Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry Aly
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. ISLPED (2019)
Houssam Zenati, Manon Romain, Chuan Sheng Foo, Bruno Lecouat, Vijay Ramaseshan Chandrasekhar
Adversarially Learned Anomaly Detection. CoRR (2018)
Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar
Semi-Supervised Learning with GANs: Revisiting Manifold Regularization. CoRR (2018)
Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. CoRR (2018)
Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar
Efficient GAN-Based Anomaly Detection. CoRR (2018)
Yasin Yazici, Chuan Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar
The Unusual Effectiveness of Averaging in GAN Training. CoRR (2018)
Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar
Semi-Supervised Learning With GANs: Revisiting Manifold Regularization. ICLR (Workshop) (2018)
Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar
Manifold regularization with GANs for semi-supervised learning. CoRR (2018)
Xiaoli Li, Chuan Sheng Foo, Kar Leong Tew, See-Kiong Ng
Searching for Rising Stars in Bibliography Networks. DASFAA (2009)