Chuan Sheng Foo

57 papers A* 14A 4B 2C 2Misc 2Journal 26Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	The Initialization Effect: Refining Bayesian Optimization for Circuit Design. IEEE Trans. Circuits Syst. Artif. Intell. Anusha James, Zhi Hui Kong, Sezin Kircali Ata, Khin Mi Mi Aung, Kiat Seng Yeo, Chuan Sheng Foo, Ashish James
2025	J	`jnl`	Confidence Elicitation: A New Attack Vector for Large Language Models. CoRR Brian Formento, Chuan Sheng Foo, See-Kiong Ng
2024	—	`conf`	3DFG-PIFu: 3D Feature Grids for Human Digitization from Sparse Views. ECCV (24) Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin
2024	J	`jnl`	COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection. CoRR Jingyi Liao, Xun Xu, Manh Cuong Nguyen, Adam Goodge, Chuan Sheng Foo
2024	J	`jnl`	COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection. IEEE Trans. Image Process. Jingyi Liao, Xun Xu, Manh Cuong Nguyen, Adam Goodge, Chuan Sheng Foo
2024	A*	`conf`	Data Distribution Valuation. NeurIPS Xinyi Xu, Shuaiqi Wang, Chuan Sheng Foo, Bryan Kian Hsiang Low, Giulia Fanti
2024	A*	`conf`	Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction. AAAI Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin
2024	J	`jnl`	Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction. CoRR Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin
2024	J	`jnl`	Label-Efficient Point Cloud Semantic Segmentation: A Holistic Active Learning Approach. World Sci. Annu. Rev. Artif. Intell. Xian Shi, Lile Cai, Ke Chen, Chuan Sheng Foo, Kui Jia, Xun Xu
2024	J	`jnl`	On Representation Knowledge Distillation for Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan Sheng Foo
2024	A*	`conf`	R-Cyclic Diffuser: Reductive and Cyclic Latent Diffusion for 3D Clothed Human Digitalization. CVPR Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin
2024	A*	`conf`	REACTO: Reconstructing Articulated Objects from a Single Video. CVPR Chaoyue Song, Jiacheng Wei, Chuan Sheng Foo, Guosheng Lin, Fayao Liu
2024	J	`jnl`	Revisiting pretraining for semi-supervised learning in the low-label regime. Neurocomputing Xun Xu, Jingyi Liao, Lile Cai, Manh Cuong Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo
2024	J	`jnl`	SemRoDe: Macro Adversarial Training to Learn Representations That are Robust to Word-Level Attacks. CoRR Brian Formento, Wenjie Feng, Chuan Sheng Foo, Luu Anh Tuan, See-Kiong Ng
2024	C	`conf`	The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design. ISCAS Sezin Kircali Ata, Zhi-Hui Kong, Anusha James, Lile Cai, Kiat Seng Yeo, Khin Mi Mi Aung, Chuan Sheng Foo, Ashish James
2024	A*	`conf`	Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline. NeurIPS Dapeng Hu, Romy Luo, Jian Liang, Chuan Sheng Foo
2024	—	`conf`	Towards Safe and Efficient Analog Circuit Design: Active Learning for Feasibility Region Exploration. APCCAS Sezin Kircali Ata, Zhi-Hui Kong, Anusha James, Lile Cai, Kiat Seng Yeo, Khin Mi Mi Aung, Chuan Sheng Foo, Ashish James
2023	A*	`conf`	Bayesian Optimization with Cost-varying Variable Subsets. NeurIPS Sebastian Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low
2023	A	`conf`	FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery. AISTATS Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, Bryan Kian Hsiang Low
2023	J	`jnl`	MoDA: Modeling Deformable 3D Objects from Casual Videos. CoRR Chaoyue Song, Tianyi Chen, Yiwen Chen, Jiacheng Wei, Chuan Sheng Foo, Fayao Liu, Guosheng Lin
2023	A*	`conf`	Model Shapley: Equitable Model Valuation with Black-box Access. NeurIPS Xinyi Xu, Thanh Lam, Chuan Sheng Foo, Bryan Kian Hsiang Low
2023	A	`conf`	No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities. AISTATS Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low
2023	Misc	`conf`	On Adversarial Robustness of Audio Classifiers. ICASSP Kangkang Lu, Manh Cuong Nguyen, Xun Xu, Chuan Sheng Foo
2023	A*	`conf`	Probably Approximate Shapley Fairness with Applications in Machine Learning. AAAI Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Bryan Kian Hsiang Low
2022	Misc	`conf`	A Minimally Supervised Approach for Medical Image Quality Assessment in Domain Shift Settings. ICASSP Huijuan Yang, Aaron S. Coyner, Feri Guretno, Ivan Ho Mien, Chuan Sheng Foo, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, Pavitra Krishnaswamy
2022	—	`conf`	Automated Deep Learning Platform for Accelerated Analog Circuit Design. SOCC Rahul Dutta, Ashish James, Salahuddin Raju, Yong-Joon Jeon, Chuan Sheng Foo, Kevin Tshun Chuan Chai
2022	C	`conf`	Bayesian Deep Active Learning for Analog Circuit Performance Classification. ISCAS Lining Zhang, Salahuddin Raju, Ashish James, Rahul Dutta, Gregoire Fournier, Damien Lancry, Kevin Chai Tshun Chuan, Vijay Ramaseshan Chandrasekhar, Chuan Sheng Foo
2022	A*	`conf`	Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity. ICML Sebastian Shenghong Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low
2022	A*	`conf`	Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards. AAAI Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low
2022	J	`jnl`	MA-GANet: A Multi-Attention Generative Adversarial Network for Defocus Blur Detection. IEEE Trans. Image Process. Zeyu Jiang, Xun Xu, Le Zhang, Chao Zhang, Chuan Sheng Foo, Ce Zhu
2022	B	`conf`	Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding. ICPR Xian Shi, Xun Xu, Wanyue Zhang, Xiatian Zhu, Chuan Sheng Foo, Kui Jia
2022	J	`jnl`	Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding. CoRR Xian Shi, Xun Xu, Wanyue Zhang, Xiatian Zhu, Chuan Sheng Foo, Kui Jia
2022	J	`jnl`	Probably Approximate Shapley Fairness with Applications in Machine Learning. CoRR Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Kian Hsiang Low
2022	J	`jnl`	Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime. CoRR Xun Xu, Jingyi Liao, Lile Cai, Cuong Manh Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo
2021	J	`jnl`	A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity Recognition. CoRR Govind Narasimman, Kangkang Lu, Arun Raja, Chuan Sheng Foo, Mohamed M. Sabry Aly, Jie Lin, Vijay Chandrasekhar
2021	J	`jnl`	Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction. IEEE Trans. Ind. Informatics Mohamed Ragab, Zhenghua Chen, Min Wu, Chuan Sheng Foo, Chee Keong Kwoh, Ruqiang Yan, Xiaoli Li
2021	—	`conf`	Genotype Imputation with Homomorphic Encryption. ICBIP Chan Fook Mun, Ahmad Qaisar, Ahmad Al Badawi, Sim Jun Jie, Benjamin Hong Meng Tan, Chuan Sheng Foo, Khin Mi Mi Aung
2021	A*	`conf`	Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning. NeurIPS Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low
2021	J	`jnl`	Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards. CoRR Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low
2021	J	`jnl`	Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach. CoRR Xian Shi, Xun Xu, Ke Chen, Lile Cai, Chuan Sheng Foo, Kui Jia
2021	A	`conf`	On Automatic Data Augmentation for 3D Point Cloud Classification. BMVC Wanyue Zhang, Xun Xu, Fayao Liu, Le Zhang, Chuan Sheng Foo
2021	A*	`conf`	Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs. CVPR Lile Cai, Xun Xu, Jun Hao Liew, Chuan Sheng Foo
2021	J	`jnl`	Semi-supervised classification of radiology images with NoTeacher: A Teacher that is not Mean. CoRR Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chao Li, Chuan Sheng Foo, Pavitra Krishnaswamy
2021	J	`jnl`	Semi-supervised classification of radiology images with NoTeacher: A teacher that is not mean. Medical Image Anal. Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chao Li, Chuan Sheng Foo, Pavitra Krishnaswamy
2021	A*	`conf`	Validation Free and Replication Robust Volume-based Data Valuation. NeurIPS Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low
2020	—	`conf`	Semi-supervised Classification of Diagnostic Radiographs with NoTeacher: A Teacher that is Not Mean. MICCAI (1) Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chuan Sheng Foo, Pavitra Krishnaswamy
2019	—	`conf`	Learning of Multi-Dimensional Analog Circuits Through Generative Adversarial Network (GAN). SoCC 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
2019	A*	`conf`	MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors. CVPR Lile Cai, Bin Zhao, Zhe Wang, Jie Lin, Chuan Sheng Foo, Mohamed M. Sabry Aly, Vijay Chandrasekhar
2019	A	`conf`	TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. ISLPED Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry Aly
2018	J	`jnl`	Adversarially Learned Anomaly Detection. CoRR Houssam Zenati, Manon Romain, Chuan Sheng Foo, Bruno Lecouat, Vijay Ramaseshan Chandrasekhar
2018	J	`jnl`	Efficient GAN-Based Anomaly Detection. CoRR Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar
2018	J	`jnl`	Manifold regularization with GANs for semi-supervised learning. CoRR Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar
2018	—	`conf`	Semi-Supervised Learning With GANs: Revisiting Manifold Regularization. ICLR (Workshop) Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar
2018	J	`jnl`	Semi-Supervised Learning with GANs: Revisiting Manifold Regularization. CoRR Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar
2018	J	`jnl`	TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks. CoRR Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry
2018	J	`jnl`	The Unusual Effectiveness of Averaging in GAN Training. CoRR Yasin Yazici, Chuan Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar
2009	B	`conf`	Searching for Rising Stars in Bibliography Networks. DASFAA Xiaoli Li, Chuan Sheng Foo, Kar Leong Tew, See-Kiong Ng