Tay, Sebastian Shenghong

4 publications

ICLR 2024 A Unified Framework for Bayesian Optimization Under Contextual Uncertainty Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low

AISTATS 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

ICML 2022 Efficient Distributionally Robust Bayesian Optimization with Worst-Case Sensitivity Sebastian Shenghong Tay, Chuan Sheng Foo, Urano Daisuke, Richalynn Leong, Bryan Kian Hsiang Low

AAAI 2022 Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards Sebastian Shenghong Tay, Xinyi Xu, Chuan Sheng Foo, Bryan Kian Hsiang Low