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Event_680x440_Areas_IIM
27Nov
Information and Innovation Management, Seminar Calendar

“Stochastic Optimization Forests” by Mr. Xiaojie Mao

Friday, 27 November, 2020 | 10:00 a.m. — 11:30 a.m.
online seminar
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SPEAKER

Mr.  Xiaojie Mao
Ph.D. Candidate in Statistics, with minor in Operations Research
Department of Statistics and Data Science
Cornell University

ABSTRACT

We study contextual stochastic optimization problems, where we leverage rich auxiliary observations (e.g., product characteristics) to improve decision making with uncertain variables (e.g., demand). We show how to train forest decision policies for this problem by growing trees that choose splits to directly optimize the downstream decision quality, rather than splitting to improve prediction accuracy as in the standard random forest algorithm. We realize this seemingly computationally intractable problem by developing approximate splitting criteria that utilize optimization perturbation analysis to eschew burdensome re-optimization for every candidate split, so that our method scales to large-scale problems. We prove that our splitting criteria consistently approximate the true risk and that our method achieves asymptotic optimality. We extensively validate our method empirically, demonstrating the value of optimization-aware construction of forests and the success of our efficient approximations. We show that our approximate splitting criteria can reduce running time hundredfold, while achieving performance close to forest algorithms that exactly re-optimize for every candidate split.

How (not) to get published

26 Nov 2020

HKU-Accenture Business Consulting Programme

Jan - Mar 2021

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Photo_Xiaojie Mao
About Speaker
Mr. Xiaojie Mao

Ph.D. Candidate in Statistics, Department of Statistics and Data Science, Cornell University

“Stochastic Optimization Forests” by Mr. Xiaojie Mao
Friday, 27 November, 202010:00 a.m. — 11:30 a.m.
online seminar
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