Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI)  

作　　者：Alexander E.Siemenn Zekun Ren Qianxiao Li Tonio Buonassisi 

机构地区：[1]Department of Mechanical Engineering,Massachusetts Institute of Technology,Cambridge,MA,USA [2]Department of Electrical and Computer Engineering,Singapore-MIT Alliance for Research and Technology,Singapore,Singapore [3]Xinterra,Singapore,Singapore [4]Department of Mathematics,National University of Singapore,Singapore,Singapore [5]Institute for Functional Intelligent Materials,National University of Singapore,Singapore,Singapore

出　　处：《npj Computational Materials》2023年第1期1543-1555,共13页计算材料学（英文）

基　　金：acknowledges support from the National Research Foundation,Singapore(project No.NRF-NRFF13-2021-0005);the Ministry of Education,Singapore,under its Research Centre of Excellence award to I-FIM(project No.EDUNC-33-18-279-V12).

摘　　要：Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction,ecological resource management,fraud detection,and material property optimization.A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dataset.However,current state-of-the-art optimization algorithms are not designed with the capabilities to find solutions to these challenging multidimensional Needle-in-a-Haystack problems,resulting in slow convergence or pigeonholing into a local minimum.In this paper,we present a Zooming Memory-Based Initialization algorithm,entitled ZoMBI,that builds on conventional Bayesian optimization principles to quickly and efficiently optimize Needle-in-a-Haystack problems in both less time and fewer experiments.The ZoMBI algorithm demonstrates compute time speed-ups of 400×compared to traditional Bayesian optimization as well as efficiently discovering optima in under 100 experiments that are up to 3×more highly optimized than those discovered by similar methods.

关 键 词：OPTIMIZATION PROBLEMS EXTREME 

分 类 号：O17[理学—数学]