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Mugs: A Multi-Granular Self-Supervised Learning Framework


Mar 27, 2022
Pan Zhou, Yichen Zhou, Chenyang Si, Weihao Yu, Teck Khim Ng, Shuicheng Yan

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* code and models are available at https://github.com/sail-sg/mugs 

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Adaptive Modeling Against Adversarial Attacks


Dec 23, 2021
Zhiwen Yan, Teck Khim Ng

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* 10 pages, 3 figures 

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SINGA-Easy: An Easy-to-Use Framework for MultiModal Analysis


Aug 03, 2021
Naili Xing, Sai Ho Yeung, Chenghao Cai, Teck Khim Ng, Wei Wang, Kaiyuan Yang, Nan Yang, Meihui Zhang, Gang Chen, Beng Chin Ooi

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* 10 pages, 10 figures 

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Enhancing Transformation-based Defenses using a Distribution Classifier


Jun 01, 2019
Connie Kou, Hwee Kuan Lee, Teck Khim Ng, Ee-Chien Chang

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An Efficient Network for Predicting Time-Varying Distributions


Nov 05, 2018
Connie Kou, Hwee Kuan Lee, Teck Khim Ng, Jorge Sanz

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A Compact Network Learning Model for Distribution Regression


Jul 10, 2018
Connie Kou, Hwee Kuan Lee, Teck Khim Ng

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PANDA: Facilitating Usable AI Development


Apr 26, 2018
Jinyang Gao, Wei Wang, Meihui Zhang, Gang Chen, H. V. Jagadish, Guoliang Li, Teck Khim Ng, Beng Chin Ooi, Sheng Wang, Jingren Zhou

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Rafiki: Machine Learning as an Analytics Service System


Apr 17, 2018
Wei Wang, Sheng Wang, Jinyang Gao, Meihui Zhang, Gang Chen, Teck Khim Ng, Beng Chin Ooi

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* 13 pages 

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