Chuan-Sheng Foo

106 papers A* 22A 3B 6Misc 1Journal 64Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Evidentially Calibrated Source-Free Time-Series Domain Adaptation With Temporal Imputation. IEEE Trans. Knowl. Data Eng. Mohamed Ragab, Peiliang Gong, Emadeldeen Eldele, Wenyu Zhang, Min Wu, Chuan-Sheng Foo, Daoqiang Zhang, Xiaoli Li, Zhenghua Chen
2026	J	`jnl`	SRNet: Self-supervised structure regularization for stereo matching. Neurocomputing Jun Cheng, Zaiwang Gu, Weide Liu, Jiayuan Fan, Zhengguo Li, Chuan-Sheng Foo
2026	J	`jnl`	The Chicken and Egg Dilemma: Co-optimizing Data and Model Configurations for LLMs. CoRR Zhiliang Chen, Alfred Wei Lun Leong, Shao Yong Ong, Apivich Hemachandra, Gregory Kang Ruey Lau, Chuan-Sheng Foo, Zhengyuan Liu, Nancy F. Chen, Bryan Kian Hsiang Low
2025	J	`jnl`	Box-Level Class-Balanced Sampling for Active Object Detection. CoRR Jingyi Liao, Xun Xu, Chuan-Sheng Foo, Lile Cai
2025	J	`jnl`	Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs using Semantic Space. CoRR Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025	A*	`conf`	Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space. ICLR Zhiliang Chen, Xinyuan Niu, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025	A*	`conf`	CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images. CVPR Cheng Chen, Jiacheng Wei, Tianrun Chen, Chi Zhang, Xiaofeng Yang, Shangzhan Zhang, Bingchen Yang, Chuan-Sheng Foo, Guosheng Lin, Qixing Huang, Fayao Liu
2025	J	`jnl`	CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images. CoRR Cheng Chen, Jiacheng Wei, Tianrun Chen, Chi Zhang, Xiaofeng Yang, Shangzhan Zhang, Bingchen Yang, Chuan-Sheng Foo, Guosheng Lin, Qixing Huang, Fayao Liu
2025	A*	`conf`	Confidence Elicitation: A New Attack Vector for Large Language Models. ICLR Brian Formento, Chuan-Sheng Foo, See-Kiong Ng
2025	J	`jnl`	DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks. CoRR Zhiliang Chen, Gregory Kang Ruey Lau, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025	A*	`conf`	Evidential Learning-based Certainty Estimation for Robust Dense Feature Matching. ICLR Lile Cai, Chuan-Sheng Foo, Xun Xu, Zaiwang Gu, Jun Cheng, XuLei Yang
2025	J	`jnl`	Exploring Active Learning for Semiconductor Defect Segmentation. CoRR Lile Cai, Ramanpreet Singh Pahwa, Xun Xu, Jie Wang, Richard Chang, Lining Zhang, Chuan-Sheng Foo
2025	J	`jnl`	Exploring Spatial Diversity for Region-based Active Learning. CoRR Lile Cai, Xun Xu, Lining Zhang, Chuan-Sheng Foo
2025	J	`jnl`	Incentivizing Time-Aware Fairness in Data Sharing. CoRR Jiangwei Chen, Kieu Thao Nguyen Pham, Rachael Hwee Ling Sim, Arun Verma, Zhaoxuan Wu, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025	J	`jnl`	Mining Semantic Correlations Between Mispredictions and Corrections for Interactive Semantic Segmentation. IEEE Trans. Neural Networks Learn. Syst. Yutong Gao, Congyan Lang, Fayao Liu, Chuan-Sheng Foo, Yuanzhouhan Cao, Lijuan Sun, Yunchao Wei
2025	J	`jnl`	MoDA: Modeling Deformable 3D Objects from Casual Videos. Int. J. Comput. Vis. Chaoyue Song, Jiacheng Wei, Tianyi Chen, Yiwen Chen, Chuan-Sheng Foo, Fayao Liu, Guosheng Lin
2025	A*	`conf`	NICE Data Selection for Instruction Tuning in LLMs with Non-differentiable Evaluation Metric. ICML Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Pang Wei Koh, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2025	A*	`conf`	On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning. ICLR Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, XuLei Yang, Chuan-Sheng Foo, Xun Xu
2025	A*	`conf`	Robust-PIFu: Robust Pixel-aligned Implicit Function for 3D Human Digitalization from a Single Image. ICLR Kennard Yanting Chan, Fayao Liu, Guosheng Lin, Chuan-Sheng Foo, Weisi Lin
2025	J	`jnl`	Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-training. Int. J. Comput. Vis. Wenyu Zhang, Li Shen, Chuan-Sheng Foo
2025	J	`jnl`	The Reward Model Selection Crisis in Personalized Alignment. CoRR Fady Rezk, Yuangang Pan, Chuan-Sheng Foo, Xun Xu, Nancy Chen, Henry Gouk, Timothy M. Hospedales
2025	—	`conf`	WASA: WAtermark-based Source Attribution for Large Language Model-Generated Data. ACL (Findings) Xinyang Lu, Jingtan Wang, Zitong Zhao, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low
2025	J	`jnl`	WaterDrum: Watermarking for Data-centric Unlearning Metric. CoRR Xinyang Lu, Xinyuan Niu, Gregory Kang Ruey Lau, Bui Thi Cam Nhung, Rachael Hwee Ling Sim, Fanyu Wen, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low
2024	A*	`conf`	A Unified Framework for Bayesian Optimization under Contextual Uncertainty. ICLR Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low
2024	B	`conf`	Box-Level Class-Balanced Sampling For Active Object Detection. ICIP Jingyi Liao, Xun Xu, Chuan-Sheng Foo, Lile Cai
2024	J	`jnl`	Data Distribution Valuation. CoRR Xinyi Xu, Shuaiqi Wang, Chuan-Sheng Foo, Bryan Kian Hsiang Low, Giulia Fanti
2024	J	`jnl`	Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation. CoRR Mohamed Ragab, Peiliang Gong, Emadeldeen Eldele, Wenyu Zhang, Min Wu, Chuan-Sheng Foo, Daoqiang Zhang, Xiaoli Li, Zhenghua Chen
2024	J	`jnl`	Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation. Int. J. Comput. Vis. Weide Liu, Zhonghua Wu, Yang Zhao, Yuming Fang, Chuan-Sheng Foo, Jun Cheng, Guosheng Lin
2024	A*	`conf`	Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions. ICML Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2024	J	`jnl`	Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions. CoRR Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2024	J	`jnl`	Hybrid Active Learning with Uncertainty-Weighted Embeddings. Trans. Mach. Learn. Res. Yinan He, Lile Cai, Jingyi Liao, Chuan-Sheng Foo
2024	—	`conf`	Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning. CAI Manas Gupta, Efe Camci, Vishandi Rudy Keneta, Abhishek Vaidyanathan, Ritwik Kanodia, Ashish James, Chuan-Sheng Foo, Min Wu, Jie Lin
2024	J	`jnl`	On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning. CoRR Yongyi Su, Yushu Li, Nanqing Liu, Kui Jia, XuLei Yang, Chuan-Sheng Foo, Xun Xu
2024	A	`conf`	PromptAD: Zero-shot Anomaly Detection using Text Prompts. WACV Yiting Li, Adam David Goodge, Fayao Liu, Chuan-Sheng Foo
2024	A*	`conf`	Pseudo-Calibration: Improving Predictive Uncertainty Estimation in Unsupervised Domain Adaptation. ICML Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo
2024	J	`jnl`	REACTO: Reconstructing Articulated Objects from a Single Video. CoRR Chaoyue Song, Jiacheng Wei, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu
2024	A*	`conf`	Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior. CVPR Cheng Chen, Xiaofeng Yang, Fan Yang, Chengzeng Feng, Zhoujie Fu, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu
2024	J	`jnl`	Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior. CoRR Cheng Chen, Xiaofeng Yang, Fan Yang, Chengzeng Feng, Zhoujie Fu, Chuan-Sheng Foo, Guosheng Lin, Fayao Liu
2024	—	`conf`	SemRoDe: Macro Adversarial Training to Learn Representations that are Robust to Word-Level Attacks. NAACL-HLT Brian Formento, Wenjie Feng, Chuan-Sheng Foo, Anh Tuan Luu, See-Kiong Ng
2024	J	`jnl`	Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-Training. CoRR Wenyu Zhang, Li Shen, Chuan-Sheng Foo
2024	A*	`conf`	Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components. ICML Zhiliang Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2024	J	`jnl`	Training neural networks with classification rules for incorporating domain knowledge. Knowl. Based Syst. Wenyu Zhang, Fayao Liu, Cuong Manh Nguyen, Zhong Liang Ou Yang, Savitha Ramasamy, Chuan-Sheng Foo
2024	J	`jnl`	Uniformly Distributed Feature Representations for Fair and Robust Learning. Trans. Mach. Learn. Res. Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo
2024	A*	`conf`	Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias. CVPR Wenyu Zhang, Qingmu Liu, Felix Ong Wei Cong, Mohamed Ragab, Chuan-Sheng Foo
2024	J	`jnl`	Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias. CoRR Wenyu Zhang, Qingmu Liu, Felix Ong Wei Cong, Mohamed Ragab, Chuan-Sheng Foo
2024	J	`jnl`	Waterfall: Framework for Robust and Scalable Text Watermarking. CoRR Gregory Kang Ruey Lau, Xinyuan Niu, Hieu Dao, Jiangwei Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2024	A*	`conf`	Waterfall: Scalable Framework for Robust Text Watermarking and Provenance for LLMs. EMNLP Gregory Kang Ruey Lau, Xinyuan Niu, Hieu Dao, Jiangwei Chen, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2024	J	`jnl`	When low-vision task meets dense prediction tasks with less data: an auxiliary self-trained geometry regularization. Trans. Mach. Learn. Res. Zaiwang Gu, Weide Liu, XuLei Yang, Chuan-Sheng Foo, Jun Cheng
2023	J	`jnl`	ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. ACM Trans. Knowl. Discov. Data Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2023	J	`jnl`	Diverse and consistent multi-view networks for semi-supervised regression. Mach. Learn. Cuong Manh Nguyen, Arun Raja, Le Zhang, Xun Xu, Balagopal Unnikrishnan, Mohamed Ragab, Kangkang Lu, Chuan-Sheng Foo
2023	A*	`conf`	Fair yet Asymptotically Equal Collaborative Learning. ICML Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2023	J	`jnl`	Fair yet Asymptotically Equal Collaborative Learning. CoRR Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng, Chuan-Sheng Foo, Bryan Kian Hsiang Low
2023	J	`jnl`	Fourier Sensitivity and Regularization of Computer Vision Models. CoRR Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo
2023	J	`jnl`	Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation. CoRR Weide Liu, Zhonghua Wu, Yang Zhao, Yuming Fang, Chuan-Sheng Foo, Jun Cheng, Guosheng Lin
2023	J	`jnl`	Mitigating Real-World Distribution Shifts in the Fourier Domain. Trans. Mach. Learn. Res. Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo
2023	J	`jnl`	PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation. CoRR Dapeng Hu, Jian Liang, Xinchao Wang, Chuan-Sheng Foo
2023	A*	`conf`	Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation. ICCV Wenyu Zhang, Li Shen, Chuan-Sheng Foo
2023	A*	`conf`	Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. KDD Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen
2023	J	`jnl`	Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. CoRR Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen
2023	—	`conf`	Using Punctuation as an Adversarial Attack on Deep Learning-Based NLP Systems: An Empirical Study. EACL (Findings) Brian Formento, Chuan-Sheng Foo, Anh Tuan Luu, See-Kiong Ng
2023	J	`jnl`	WASA: WAtermark-based Source Attribution for Large Language Model-Generated Data. CoRR Jingtan Wang, Xinyang Lu, Zitong Zhao, Zhongxiang Dai, Chuan-Sheng Foo, See-Kiong Ng, Bryan Kian Hsiang Low
2022	J	`jnl`	ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series Data. CoRR Mohamed Ragab, Emadeldeen Eldele, Wee Ling Tan, Chuan-Sheng Foo, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li
2022	J	`jnl`	An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series. IEEE Trans. Neural Networks Learn. Syst. Astha Garg, Wenyu Zhang, Jules Samaran, Ramasamy Savitha, Chuan-Sheng Foo
2022	J	`jnl`	Classify and generate: Using classification latent space representations for image generations. Neurocomputing Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi
2022	J	`jnl`	Co-Learning with Pre-Trained Networks Improves Source-Free Domain Adaptation. CoRR Wenyu Zhang, Li Shen, Chuan-Sheng Foo
2022	B	`conf`	Domain Generalization via Selective Consistency Regularization for Time Series Classification. ICPR Wenyu Zhang, Mohamed Ragab, Chuan-Sheng Foo
2022	J	`jnl`	Domain Generalization via Selective Consistency Regularization for Time Series Classification. CoRR Wenyu Zhang, Mohamed Ragab, Chuan-Sheng Foo
2022	B	`conf`	Exploring Active Learning for Semiconductor Defect Segmentation. ICIP Lile Cai, Ramanpreet Singh Pahwa, Xun Xu, Jie Wang, Richard Chang, Lining Zhang, Chuan-Sheng Foo
2022	A*	`conf`	Few-Shot Adaptation of Pre-Trained Networks for Domain Shift. IJCAI Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo
2022	J	`jnl`	Few-Shot Adaptation of Pre-Trained Networks for Domain Shift. CoRR Wenyu Zhang, Li Shen, Wanyue Zhang, Chuan-Sheng Foo
2022	J	`jnl`	Fourier Sensitivity and Regularization of Computer Vision Models. Trans. Mach. Learn. Res. Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo
2022	J	`jnl`	Is Complexity Required for Neural Network Pruning? A Case Study on Global Magnitude Pruning. CoRR Manas Gupta, Efe Camci, Vishandi Rudy Keneta, Abhishek Vaidyanathan, Ritwik Kanodia, Chuan-Sheng Foo, Min Wu, Jie Lin
2022	B	`conf`	Mixed Membership Generative Adversarial Networks. ICIP Yasin Yazici, Bruno Lecouat, Kim-Hui Yap, Stefan Winkler, Georgios Piliouras, Vijay Chandrasekhar, Chuan-Sheng Foo
2022	—	`conf`	Point Discriminative Learning for Data-efficient 3D Point Cloud Analysis. 3DV Fayao Liu, Guosheng Lin, Chuan-Sheng Foo, Chaitanya K. Joshi, Jie Lin
2022	J	`jnl`	Scalable and Practical Natural Gradient for Large-Scale Deep Learning. IEEE Trans. Pattern Anal. Mach. Intell. Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota
2022	J	`jnl`	SemiCurv: Semi-Supervised Curvilinear Structure Segmentation. CoRR Xun Xu, Manh Cuong Nguyen, Yasin Yazici, Kangkang Lu, Hlaing Min, Chuan-Sheng Foo
2022	J	`jnl`	SemiCurv: Semi-Supervised Curvilinear Structure Segmentation. IEEE Trans. Image Process. Xun Xu, Cuong Manh Nguyen, Yasin Yazici, Kangkang Lu, Hlaing Min, Chuan-Sheng Foo
2021	A*	`conf`	ARMOURED: Adversarially Robust MOdels using Unlabeled data by REgularizing Diversity. ICLR Kangkang Lu, Cuong Manh Nguyen, Xun Xu, Kiran Chari, Yu Jing Goh, Chuan-Sheng Foo
2021	J	`jnl`	An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series. CoRR Astha Garg, Wenyu Zhang, Jules Samaran, Savitha Ramasamy, Chuan-Sheng Foo
2021	J	`jnl`	Exploring Spatial Diversity for Region-Based Active Learning. IEEE Trans. Image Process. Lile Cai, Xun Xu, Lining Zhang, Chuan-Sheng Foo
2021	J	`jnl`	On Automatic Data Augmentation for 3D Point Cloud Classification. CoRR Wanyue Zhang, Xun Xu, Fayao Liu, Le Zhang, Chuan-Sheng Foo
2021	J	`jnl`	On Representation Knowledge Distillation for Graph Neural Networks. CoRR Chaitanya K. Joshi, Fayao Liu, Xu Xun, Jie Lin, Chuan-Sheng Foo
2021	J	`jnl`	Point Discriminative Learning for Unsupervised Representation Learning on 3D Point Clouds. CoRR Fayao Liu, Guosheng Lin, Chuan-Sheng Foo
2021	B	`conf`	Special Symbol Attacks On NLP Systems. IJCNN Brian Formento, See-Kiong Ng, Chuan-Sheng Foo
2020	J	`jnl`	Classification Representations Can be Reused for Downstream Generations. CoRR Saisubramaniam Gopalakrishnan, Pranshu Ranjan Singh, Yasin Yazici, Chuan-Sheng Foo, Vijay Chandrasekhar, Arulmurugan Ambikapathi
2020	B	`conf`	Empirical Analysis Of Overfitting And Mode Drop In Gan Training. ICIP Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar
2020	J	`jnl`	Empirical Analysis of Overfitting and Mode Drop in GAN Training. CoRR Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Vijay Chandrasekhar
2020	J	`jnl`	Holistic Multi-Modal Memory Network for Movie Question Answering. IEEE Trans. Image Process. Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar
2020	Misc	`conf`	Mahalanobis Distance Based Adversarial Network for Anomaly Detection. ICASSP Yubo Hou, Zhenghua Chen, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Raed M. Shubair
2020	J	`jnl`	Scalable and Practical Natural Gradient for Large-Scale Deep Learning. CoRR Kazuki Osawa, Yohei Tsuji, Yuichiro Ueno, Akira Naruse, Chuan-Sheng Foo, Rio Yokota
2019	J	`jnl`	Learning to Impute: A General Framework for Semi-supervised Learning. CoRR Wei-Hong Li, Chuan-Sheng Foo, Hakan Bilen
2019	—	`conf`	Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile. ICLR (Poster) Panayotis Mertikopoulos, Bruno Lecouat, Houssam Zenati, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras
2019	A	`conf`	Semi-Supervised Audio Classification with Consistency-Based Regularization. INTERSPEECH Kangkang Lu, Chuan-Sheng Foo, Kah Kuan Teh, Huy Dat Tran, Vijay Ramaseshan Chandrasekhar
2019	—	`conf`	The Unusual Effectiveness of Averaging in GAN Training. ICLR (Poster) Yasin Yazici, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar
2019	—	`conf`	Towards Practical Unsupervised Anomaly Detection on Retinal Images. DART/MIL3ID@MICCAI 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
2019	J	`jnl`	Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions. CoRR Yasin Yazici, Bruno Lecouat, Chuan-Sheng Foo, Stefan Winkler, Kim-Hui Yap, Georgios Piliouras, Vijay Chandrasekhar
2018	A*	`conf`	Adversarially Learned Anomaly Detection. ICDM Houssam Zenati, Manon Romain, Chuan-Sheng Foo, Bruno Lecouat, Vijay Chandrasekhar
2018	J	`jnl`	Holistic Multi-modal Memory Network for Movie Question Answering. CoRR Anran Wang, Anh Tuan Luu, Chuan-Sheng Foo, Hongyuan Zhu, Yi Tay, Vijay Chandrasekhar
2018	J	`jnl`	Mirror descent in saddle-point problems: Going the extra (gradient) mile. CoRR Panayotis Mertikopoulos, Houssam Zenati, Bruno Lecouat, Chuan-Sheng Foo, Vijay Chandrasekhar, Georgios Piliouras
2018	J	`jnl`	Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials. CoRR Léo Laugier, Daniil Bash, Jose Recatala, Hong Kuan Ng, Savitha Ramasamy, Chuan-Sheng Foo, Vijay Ramaseshan Chandrasekhar, Kedar Hippalgaonkar
2018	J	`jnl`	Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. CoRR Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy
2017	—	`—`	Machine learning models for analyzing chromatin and RNA structure data. Chuan-Sheng Foo
2009	A*	`conf`	A majorization-minimization algorithm for (multiple) hyperparameter learning. ICML Chuan-Sheng Foo, Chuong B. Do, Andrew Y. Ng
2009	A*	`conf`	Proximal regularization for online and batch learning. ICML Chuong B. Do, Quoc V. Le, Chuan-Sheng Foo
2008	A	`conf`	A max-margin model for efficient simultaneous alignment and folding of RNA sequences. ISMB Chuong B. Do, Chuan-Sheng Foo, Serafim Batzoglou
2007	—	`conf`	Efficient multiple hyperparameter learning for log-linear models. NIPS Chuong B. Do, Chuan-Sheng Foo, Andrew Y. Ng