Chuan-Sheng Foo

According to our database, Chuan-Sheng Foo authored at least 108 papers between 2007 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Mining Semantic Correlations Between Mispredictions and Corrections for Interactive Semantic Segmentation.

Yutong Gao, Congyan Lang, Fayao Liu, Chuan-Sheng Foo, Yuanzhouhan Cao, Lijuan Sun, Yunchao Wei

IEEE Trans. Neural Networks Learn. Syst., March, 2025

Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-training.

Wenyu Zhang, Li Shen, Chuan-Sheng Foo

Int. J. Comput. Vis., February, 2025

Confidence Elicitation: A New Attack Vector for Large Language Models.

Brian Formento, Chuan Sheng Foo, See-Kiong Ng

CoRR, February, 2025

DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks.

Zhiliang Chen, Gregory Kang Ruey Lau, Chuan-Sheng Foo, Bryan Kian Hsiang Low

CoRR, February, 2025

2024

On Representation Knowledge Distillation for Graph Neural Networks.

Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan Sheng Foo

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation.

Weide Liu, Zhonghua Wu, Yang Zhao, Yuming Fang, Chuan-Sheng Foo, Jun Cheng, Guosheng Lin

Int. J. Comput. Vis., April, 2024

Revisiting pretraining for semi-supervised learning in the low-label regime.

Xun Xu, Jingyi Liao, Lile Cai, Manh Cuong Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo

Neurocomputing, January, 2024

Label-Efficient Point Cloud Semantic Segmentation: A Holistic Active Learning Approach.

Xian Shi, Lile Cai, Ke Chen, Chuan Sheng Foo, Kui Jia, Xun Xu

World Sci. Annu. Rev. Artif. Intell., 2024

Hybrid Active Learning with Uncertainty-Weighted Embeddings.

Yinan He, Lile Cai, Jingyi Liao, Chuan-Sheng Foo

Trans. Mach. Learn. Res., 2024

COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection.

Jingyi Liao, Xun Xu, Manh Cuong Nguyen, Adam Goodge, Chuan Sheng Foo

IEEE Trans. Image Process., 2024

Training neural networks with classification rules for incorporating domain knowledge.

Wenyu Zhang, Fayao Liu, Cuong Manh Nguyen, Zhong Liang Ou Yang, Savitha Ramasamy, Chuan-Sheng Foo

Knowl. Based Syst., 2024

On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning.

Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, Xulei Yang, Chuan-Sheng Foo, Xun Xu

CoRR, 2024

Waterfall: Framework for Robust and Scalable Text Watermarking.

Gregory Kang Ruey Lau, Xinyuan Niu, Hieu Dao, Jiangwei Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low

CoRR, 2024

Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation.

Mohamed Ragab, Peiliang Gong, Emadeldeen Eldele, Wenyu Zhang, Min Wu, Chuan-Sheng Foo, Daoqiang Zhang, Xiaoli Li, Zhenghua Chen

CoRR, 2024

PromptAD: Zero-shot Anomaly Detection using Text Prompts.

Yiting Li, Adam David Goodge, Fayao Liu, Chuan-Sheng Foo

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Data Distribution Valuation.

Xinyi Xu, Shuaiqi Wang, Chuan Sheng Foo, Bryan Kian Hsiang Low, Giulia Fanti

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Towards Reliable Model Selection for Unsupervised Domain Adaptation: An Empirical Study and A Certified Baseline.

Dapeng Hu, Romy Luo, Jian Liang, Chuan Sheng Foo

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

SemRoDe: Macro Adversarial Training to Learn Representations that are Robust to Word-Level Attacks.

Brian Formento, Wenjie Feng, Chuan-Sheng Foo, Anh Tuan Luu, See-Kiong Ng

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

The Initialization Factor: Understanding its Impact on Active Learning for Analog Circuit Design.

Sezin Kircali Ata, Zhi-Hui Kong, Anusha James, Lile Cai, Kiat Seng Yeo, Khin Mi Mi Aung, Chuan Sheng Foo, Ashish James

Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions.

Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation.

Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components.

Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Forty-first International Conference on Machine Learning, 2024

A Unified Framework for Bayesian Optimization under Contextual Uncertainty.

Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Waterfall: Scalable Framework for Robust Text Watermarking and Provenance for LLMs.

Gregory Kang Ruey Lau, Xinyuan Niu, Hieu Dao, Jiangwei Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

3DFG-PIFu: 3D Feature Grids for Human Digitization from Sparse Views.

Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin

Proceedings of the Computer Vision - ECCV 2024, 2024

REACTO: Reconstructing Articulated Objects from a Single Video.

Chaoyue Song, Jiacheng Wei, Chuan Sheng Foo, Guosheng Lin, Fayao Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior.

Cheng Chen, Xiaofeng Yang, Fan Yang, Chengzeng Feng, Zhoujie Fu, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

R-Cyclic Diffuser: Reductive and Cyclic Latent Diffusion for 3D Clothed Human Digitalization.

Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias.

Wenyu Zhang, Qingmu Liu, Felix Ong Wei Cong, Mohamed Ragab, Chuan-Sheng Foo

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Towards Safe and Efficient Analog Circuit Design: Active Learning for Feasibility Region Exploration.

Sezin Kircali Ata, Zhi-Hui Kong, Anusha James, Lile Cai, Kiat Seng Yeo, Khin Mi Mi Aung, Chuan Sheng Foo, Ashish James

Proceedings of the IEEE Asia Pacific Conference on Circuits and Systems, 2024

Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction.

Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan Sheng Foo, Weisi Lin

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Diverse and consistent multi-view networks for semi-supervised regression.

Cuong Manh Nguyen, Arun Raja, Le Zhang, Xun Xu, Balagopal Unnikrishnan, Mohamed Ragab, Kangkang Lu, Chuan-Sheng Foo

Mach. Learn., July, 2023

Mitigating Real-World Distribution Shifts in the Fourier Domain.

Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo

Trans. Mach. Learn. Res., 2023

ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data.

Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li

ACM Trans. Knowl. Discov. Data, 2023

WASA: WAtermark-based Source Attribution for Large Language Model-Generated Data.

Jingtan Wang, Xinyang Lu, Zitong Zhao, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low

CoRR, 2023

PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation.

Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo

CoRR, 2023

MoDA: Modeling Deformable 3D Objects from Casual Videos.

Chaoyue Song, Tianyi Chen, Yiwen Chen, Jiacheng Wei, Chuan Sheng Foo, Fayao Liu, Guosheng Lin

CoRR, 2023

Model Shapley: Equitable Model Valuation with Black-box Access.

Xinyi Xu, Thanh Lam, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bayesian Optimization with Cost-varying Variable Subsets.

Sebastian Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Source-Free Domain Adaptation with Temporal Imputation for Time Series Data.

Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Fair yet Asymptotically Equal Collaborative Learning.

Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the International Conference on Machine Learning, 2023

Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation.

Wenyu Zhang, Li Shen, Chuan-Sheng Foo

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

On Adversarial Robustness of Audio Classifiers.

Kangkang Lu, Manh Cuong Nguyen, Xun Xu, Chuan Sheng Foo

Proceedings of the IEEE International Conference on Acoustics, 2023

Using Punctuation as an Adversarial Attack on Deep Learning-Based NLP Systems: An Empirical Study.

Brian Formento, Chuan-Sheng Foo, Anh Tuan Luu, See-Kiong Ng

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

FAIR: Fair Collaborative Active Learning with Individual Rationality for Scientific Discovery.

Xinyi Xu, Zhaoxuan Wu, Arun Verma, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities.

Sebastian Shenghong Tay, Quoc Phong Nguyen, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Probably Approximate Shapley Fairness with Applications in Machine Learning.

Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series.

Astha Garg, Wenyu Zhang, Jules Samaran, Ramasamy Savitha, Chuan-Sheng Foo

IEEE Trans. Neural Networks Learn. Syst., 2022

Fourier Sensitivity and Regularization of Computer Vision Models.

Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo

Trans. Mach. Learn. Res., 2022

SemiCurv: Semi-Supervised Curvilinear Structure Segmentation.

Xun Xu, Cuong Manh Nguyen, Yasin Yazici, Kangkang Lu, Hlaing Min, Chuan-Sheng Foo

IEEE Trans. Image Process., 2022

MA-GANet: A Multi-Attention Generative Adversarial Network for Defocus Blur Detection.

Zeyu Jiang, Xun Xu, Le Zhang, Chao Zhang, Chuan Sheng Foo, Ce Zhu

IEEE Trans. Image Process., 2022

Scalable and Practical Natural Gradient for Large-Scale Deep Learning.

Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Classify and generate: Using classification latent space representations for image generations.

Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi

Neurocomputing, 2022

Co-Learning with Pre-Trained Networks Improves Source-Free Domain Adaptation.

Wenyu Zhang, Li Shen, Chuan-Sheng Foo

CoRR, 2022

Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning.

Manas Gupta, Efe Camci, Vishandi Rudy Keneta, Abhishek Vaidyanathan, Ritwik Kanodia, Chuan-Sheng Foo, Min Wu, Jie Lin

CoRR, 2022

SemiCurv: Semi-Supervised Curvilinear Structure Segmentation.

Xun Xu, Manh Cuong Nguyen, Yasin Yazici, Kangkang Lu, Hlaing Min, Chuan-Sheng Foo

CoRR, 2022

Revisiting Pretraining for Semi-Supervised Learning in the Low-Label Regime.

Xun Xu, Jingyi Liao, Lile Cai, Cuong Manh Nguyen, Kangkang Lu, Wanyue Zhang, Yasin Yazici, Chuan Sheng Foo

CoRR, 2022

Automated Deep Learning Platform for Accelerated Analog Circuit Design.

Rahul Dutta, Ashish James, Salahuddin Raju, Yong-Joon Jeon, Chuan Sheng Foo, Kevin Tshun Chuan Chai

Proceedings of the 35th IEEE International System-on-Chip Conference, 2022

Bayesian Deep Active Learning for Analog Circuit Performance Classification.

Lining Zhang, Salahuddin Raju, Ashish James, Rahul Dutta, Gregoire Fournier, Damien Lancry, Kevin Chai Tshun Chuan, Vijay Ramaseshan Chandrasekhar, Chuan Sheng Foo

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

Few-Shot Adaptation of Pre-Trained Networks for Domain Shift.

Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding.

Xian Shi, Xun Xu, Wanyue Zhang, Xiatian Zhu, Chuan Sheng Foo, Kui Jia

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Domain Generalization via Selective Consistency Regularization for Time Series Classification.

Wenyu Zhang, Mohamed Ragab, Chuan-Sheng Foo

Proceedings of the 26th International Conference on Pattern Recognition, 2022

Efficient Distributionally Robust Bayesian Optimization with Worst-case Sensitivity.

Sebastian Shenghong Tay, Chuan Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low

Proceedings of the International Conference on Machine Learning, 2022

Mixed Membership Generative Adversarial Networks.

Yasin Yazici, Bruno Lecouat, Kim-Hui Yap, Stefan Winkler, Georgios Piliouras, Vijay Chandrasekhar, Chuan-Sheng Foo

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Exploring Active Learning for Semiconductor Defect Segmentation.

Lile Cai, Ramanpreet Singh Pahwa, Xun Xu, Jie Wang, Richard Chang, Lining Zhang, Chuan-Sheng Foo

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

A Minimally Supervised Approach for Medical Image Quality Assessment in Domain Shift Settings.

Huijuan Yang, Aaron S. Coyner, Feri Guretno, Ivan Ho Mien, Chuan Sheng Foo, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, Pavitra Krishnaswamy

Proceedings of the IEEE International Conference on Acoustics, 2022

Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards.

Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Point Discriminative Learning for Data-efficient 3D Point Cloud Analysis.

Fayao Liu, Guosheng Lin, Chuan-Sheng Foo, Chaitanya K. Joshi, Jie Lin

Proceedings of the International Conference on 3D Vision, 2022

2021

Exploring Spatial Diversity for Region-Based Active Learning.

Lile Cai, Xun Xu, Lining Zhang, Chuan-Sheng Foo

IEEE Trans. Image Process., 2021

Contrastive Adversarial Domain Adaptation for Machine Remaining Useful Life Prediction.

Mohamed Ragab, Zhenghua Chen, Min Wu, Chuan Sheng Foo, Chee Keong Kwoh, Ruqiang Yan, Xiaoli Li

IEEE Trans. Ind. Informatics, 2021

Semi-supervised classification of radiology images with NoTeacher: A teacher that is not mean.

Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chao Li, Chuan Sheng Foo, Pavitra Krishnaswamy

Medical Image Anal., 2021

An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series.

Astha Garg, Wenyu Zhang, Jules Samaran, Savitha Ramasamy, Chuan-Sheng Foo

CoRR, 2021

Point Discriminative Learning for Unsupervised Representation Learning on 3D Point Clouds.

Fayao Liu, Guosheng Lin, Chuan-Sheng Foo

CoRR, 2021

Label-Efficient Point Cloud Semantic Segmentation: An Active Learning Approach.

Xian Shi, Xun Xu, Ke Chen, Lile Cai, Chuan Sheng Foo, Kui Jia

CoRR, 2021

A*HAR: A New Benchmark towards Semi-supervised learning for Class-imbalanced Human Activity Recognition.

Govind Narasimman, Kangkang Lu, Arun Raja, Chuan Sheng Foo, Mohamed M. Sabry Aly, Jie Lin, Vijay Chandrasekhar

CoRR, 2021

Validation Free and Replication Robust Volume-based Data Valuation.

Xinyi Xu, Zhaoxuan Wu, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Gradient Driven Rewards to Guarantee Fairness in Collaborative Machine Learning.

Xinyi Xu, Lingjuan Lyu, Xingjun Ma, Chenglin Miao, Chuan Sheng Foo, Bryan Kian Hsiang Low

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Special Symbol Attacks On NLP Systems.

Brian Formento, See-Kiong Ng, Chuan-Sheng Foo

Proceedings of the International Joint Conference on Neural Networks, 2021

ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity.

Kangkang Lu, Cuong Manh Nguyen, Xun Xu, Kiran Chari, Yu Jing Goh, Chuan-Sheng Foo

Proceedings of the 9th International Conference on Learning Representations, 2021

Revisiting Superpixels for Active Learning in Semantic Segmentation With Realistic Annotation Costs.

Lile Cai, Xun Xu, Jun Hao Liew, Chuan Sheng Foo

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

On Automatic Data Augmentation for 3D Point Cloud Classification.

Wanyue Zhang, Xun Xu, Fayao Liu, Le Zhang, Chuan Sheng Foo

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Holistic Multi-Modal Memory Network for Movie Question Answering.

Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar

IEEE Trans. Image Process., 2020

Classification Representations Can be Reused for Downstream Generations.

Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi

CoRR, 2020

Semi-supervised Classification of Diagnostic Radiographs with NoTeacher: A Teacher that is Not Mean.

Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chuan Sheng Foo, Pavitra Krishnaswamy

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Empirical Analysis Of Overfitting And Mode Drop In Gan Training.

Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar

Proceedings of the IEEE International Conference on Image Processing, 2020

Mahalanobis Distance Based Adversarial Network for Anomaly Detection.

Yubo Hou, Zhenghua Chen, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Raed M. Shubair

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Learning to Impute: A General Framework for Semi-supervised Learning.

Wei-Hong Li, Chuan-Sheng Foo, Hakan Bilen

CoRR, 2019

Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions.

Yasin Yazici, Bruno Lecouat, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar

CoRR, 2019

Learning of Multi-Dimensional Analog Circuits Through Generative Adversarial Network (GAN).

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

Proceedings of the 32nd IEEE International System-on-Chip Conference, 2019

Towards Practical Unsupervised Anomaly Detection on Retinal Images.

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

Proceedings of the Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data, 2019

TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks.

Lile Cai, Anne-Maelle Barneche, Arthur Herbout, Chuan Sheng Foo, Jie Lin, Vijay Ramaseshan Chandrasekhar, Mohamed M. Sabry Aly

Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

Semi-Supervised Audio Classification with Consistency-Based Regularization.

Kangkang Lu, Chuan-Sheng Foo, Kah Kuan Teh, Huy Dat Tran, Vijay Ramaseshan Chandrasekhar

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

The Unusual Effectiveness of Averaging in GAN Training.

Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar

Proceedings of the 7th International Conference on Learning Representations, 2019

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile.

Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

Proceedings of the 7th International Conference on Learning Representations, 2019

MaxpoolNMS: Getting Rid of NMS Bottlenecks in Two-Stage Object Detectors.

Lile Cai, Bin Zhao, Zhe Wang, Jie Lin, Chuan Sheng Foo, Mohamed M. Sabry Aly, Vijay Chandrasekhar

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images.

Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy

CoRR, 2018

Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials.

Léo Laugier, Daniil Bash, Jose Recatala, Hong Kuan Ng, Savitha Ramasamy, Chuan-Sheng Foo, Vijay Ramaseshan Chandrasekhar, Kedar Hippalgaonkar

CoRR, 2018

Manifold regularization with GANs for semi-supervised learning.

Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Chandrasekhar

CoRR, 2018

Mirror descent in saddle-point problems: Going the extra (gradient) mile.

Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras

CoRR, 2018

Efficient GAN-Based Anomaly Detection.

Houssam Zenati, Chuan Sheng Foo, Bruno Lecouat, Gaurav Manek, Vijay Ramaseshan Chandrasekhar

CoRR, 2018

Semi-Supervised Learning With GANs: Revisiting Manifold Regularization.

Bruno Lecouat, Chuan Sheng Foo, Houssam Zenati, Vijay Ramaseshan Chandrasekhar

Proceedings of the 6th International Conference on Learning Representations, 2018

Adversarially Learned Anomaly Detection.

Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

Machine learning models for analyzing chromatin and RNA structure data.

Chuan-Sheng Foo

PhD thesis, 2017

2009

A majorization-minimization algorithm for (multiple) hyperparameter learning.

Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Proximal regularization for online and batch learning.

Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Searching for Rising Stars in Bibliography Networks.

Xiaoli Li, Chuan Sheng Foo, Kar Leong Tew, See-Kiong Ng

Proceedings of the Database Systems for Advanced Applications, 2009

2008

A max-margin model for efficient simultaneous alignment and folding of RNA sequences.

Chuong B. Do, Chuan-Sheng Foo, Serafim Batzoglou

Proceedings of the Proceedings 16th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2008

2007

Efficient multiple hyperparameter learning for log-linear models.

Chuong B. Do, Chuan-Sheng Foo, Andrew Y. Ng

Proceedings of the Advances in Neural Information Processing Systems 20, 2007