1 code implementation • 11 Oct 2023 • Mingcheng Chen, Haoran Zhao, Yuxiang Zhao, Hulei Fan, Hongqiao Gao, Yong Yu, Zheng Tian
Data-driven black-box model-based optimization (MBO) problems arise in a great number of practical application scenarios, where the goal is to find a design over the whole space maximizing a black-box target function based on a static offline dataset.
1 code implementation • 16 Aug 2021 • Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao, Weinan Zhang, Xiawei Guo, Jian Shen, Yanru Qu, Jieli Lu, Min Xu, Yu Xu, Tiange Wang, Mian Li, Wei-Wei Tu, Yong Yu, Yufang Bi, Weiqing Wang, Guang Ning
To tackle the above challenges, we employ gradient boosting decision trees (GBDT) to handle data heterogeneity and introduce multi-task learning (MTL) to solve data insufficiency.
no code implementations • NeurIPS 2016 • Xinyun Chen, Chang Liu, Richard Shin, Dawn Song, Mingcheng Chen
Automatic translation from natural language descriptions into programs is a longstanding challenging problem.