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CAN-PINN: A Fast Physics-Informed Neural Network Based on Coupled-Automatic-Numerical Differentiation Method


Oct 29, 2021
Pao-Hsiung Chiu, Jian Cheng Wong, Chinchun Ooi, My Ha Dao, Yew-Soon Ong

* 24 pages, 18 figures 

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Half a Dozen Real-World Applications of Evolutionary Multitasking and More


Sep 29, 2021
Abhishek Gupta, Lei Zhou, Yew-Soon Ong, Zefeng Chen, Yaqing Hou


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Learning in Sinusoidal Spaces with Physics-Informed Neural Networks


Sep 20, 2021
Jian Cheng Wong, Chinchun Ooi, Abhishek Gupta, Yew-Soon Ong

* Currently under review 

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Word2Pix: Word to Pixel Cross Attention Transformer in Visual Grounding


Jul 31, 2021
Heng Zhao, Joey Tianyi Zhou, Yew-Soon Ong


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Multi-Party Dual Learning


Apr 14, 2021
Maoguo Gong, Yuan Gao, Yu Xie, A. K. Qin, Ke Pan, Yew-Soon Ong

* submitted to IEEE Transactions on Cybernetics 

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RNA Alternative Splicing Prediction with Discrete Compositional Energy Network


Mar 07, 2021
Alvin Chan, Anna Korsakova, Yew-Soon Ong, Fernaldo Richtia Winnerdy, Kah Wai Lim, Anh Tuan Phan

* ACM CHIL 2021 Camera-Ready 

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Multi-Space Evolutionary Search for Large-Scale Optimization


Feb 24, 2021
Liang Feng, Qingxia Shang, Yaqing Hou, Kay Chen Tan, Yew-Soon Ong


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Graph Joint Attention Networks


Feb 05, 2021
Tiantian He, Lu Bai, Yew-Soon Ong

* Working manuscript, 21 pages, 3 figures 

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Can Transfer Neuroevolution Tractably Solve Your Differential Equations?


Jan 06, 2021
Jian Cheng Wong, Abhishek Gupta, Yew-Soon Ong

* Currently under review at IEEE Computational Intelligence Magazine 

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Scalable Transfer Evolutionary Optimization: Coping with Big Task Instances


Dec 03, 2020
Mojtaba Shakeri, Erfan Miahi, Abhishek Gupta, Yew-Soon Ong

* 12 pages, 5 figures, 2 tables, 2 algorithm pseudocodes 

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Poison Attacks against Text Datasets with Conditional Adversarially Regularized Autoencoder


Oct 06, 2020
Alvin Chan, Yi Tay, Yew-Soon Ong, Aston Zhang

* Accepted in EMNLP-Findings 2020, Camera Ready Version 

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Modulating Scalable Gaussian Processes for Expressive Statistical Learning


Aug 29, 2020
Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

* 31 pages, 9 figures, 4 tables, preprint under review 

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Defending Adversarial Attacks without Adversarial Attacks in Deep Reinforcement Learning


Aug 14, 2020
Xinghua Qu, Yew-Soon Ong, Abhishek Gupta, Zhu Sun


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CoCon: A Self-Supervised Approach for Controlled Text Generation


Jun 05, 2020
Alvin Chan, Yew-Soon Ong, Bill Pung, Aston Zhang, Jie Fu


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Deep Latent-Variable Kernel Learning


May 18, 2020
Haitao Liu, Yew-Soon Ong, Xiaomo Jiang, Xiaofang Wang

* 12 pages, 8 figures, preprint under review 

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Heterogeneous Representation Learning: A Review


Apr 30, 2020
Joey Tianyi Zhou, Xi Peng, Yew-Soon Ong


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What it Thinks is Important is Important: Robustness Transfers through Input Gradients


Dec 11, 2019
Alvin Chan, Yi Tay, Yew-Soon Ong


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Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy


Nov 22, 2019
Xinghua Qu, Zhu Sun, Yew-Soon Ong, Pengfei Wei, Abhishek Gupta


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A Multi-Task Gradient Descent Method for Multi-Label Learning


Nov 19, 2019
Lu Bai, Yew-Soon Ong, Tiantian He, Abhishek Gupta


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Poison as a Cure: Detecting & Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks


Nov 19, 2019
Alvin Chan, Yew-Soon Ong


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Scalable Gaussian Process Classification with Additive Noise for Various Likelihoods


Sep 14, 2019
Haitao Liu, Yew-Soon Ong, Ziwei Yu, Jianfei Cai, Xiaobo Shen

* 11 pages, 5 figures, preprint under review 

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AIR5: Five Pillars of Artificial Intelligence Research


Jan 02, 2019
Yew-Soon Ong, Abhishek Gupta

* 5 pages, 0 figures 

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A Survey on Multi-output Learning


Jan 02, 2019
Donna Xu, Yaxin Shi, Ivor W. Tsang, Yew-Soon Ong, Chen Gong, Xiaobo Shen


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Large-scale Heteroscedastic Regression via Gaussian Process


Nov 03, 2018
Haitao Liu, Yew-Soon Ong, Jianfei Cai

* 13 pages, 13 figures 

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Understanding and Comparing Scalable Gaussian Process Regression for Big Data


Nov 03, 2018
Haitao Liu, Jianfei Cai, Yew-Soon Ong, Yi Wang

* 25 pages, 15 figures, preprint submitted to KBS 

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When Gaussian Process Meets Big Data: A Review of Scalable GPs


Jul 03, 2018
Haitao Liu, Yew-Soon Ong, Xiaobo Shen, Jianfei Cai


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Co-evolutionary multi-task learning for dynamic time series prediction


Jun 13, 2018
Rohitash Chandra, Yew-Soon Ong, Chi-Keong Goh

* Applied Soft Computing 

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Generalized Robust Bayesian Committee Machine for Large-scale Gaussian Process Regression


Jun 03, 2018
Haitao Liu, Jianfei Cai, Yi Wang, Yew-Soon Ong

* paper + supplementary material, appears in Proceedings of ICML 2018 

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