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Kian Hsiang Low

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Probably Approximate Shapley Fairness with Applications in Machine Learning

Dec 01, 2022
Zijian Zhou, Xinyi Xu, Rachael Hwee Ling Sim, Chuan Sheng Foo, Kian Hsiang Low

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Federated Bayesian Optimization via Thompson Sampling

Oct 22, 2020
Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet

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R2-B2: Recursive Reasoning-Based Bayesian Optimization for No-Regret Learning in Games

Jun 30, 2020
Zhongxiang Dai, Yizhou Chen, Kian Hsiang Low, Patrick Jaillet, Teck-Hua Ho

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Nonmyopic Gaussian Process Optimization with Macro-Actions

Feb 22, 2020
Dmitrii Kharkovskii, Chun Kai Ling, Kian Hsiang Low

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Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression

Dec 05, 2019
Tong Teng, Jie Chen, Yehong Zhang, Kian Hsiang Low

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Inverse Reinforcement Learning with Missing Data

Nov 16, 2019
Tien Mai, Quoc Phong Nguyen, Kian Hsiang Low, Patrick Jaillet

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Implicit Posterior Variational Inference for Deep Gaussian Processes

Oct 26, 2019
Haibin Yu, Yizhou Chen, Zhongxiang Dai, Kian Hsiang Low, Patrick Jaillet

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Bayesian Optimization with Binary Auxiliary Information

Jun 17, 2019
Yehong Zhang, Zhongxiang Dai, Kian Hsiang Low

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