Lei Sun
University at Buffalo
18 Papers
25 Citations
Lei Sun is an academic researcher from University at Buffalo. The author has contributed to research in topics: Travelling salesman problem & Supply chain. The author has an hindex of 7, co-authored 18 publications. Previous affiliations of Lei Sun include Praxair & State University of New York System.
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Papers
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data
TL;DR: Adversarial Balancing-based representation learning for Causal Effect Inference (ABCEI) uses adversarial learning to balance the distributions of treatment and control group in the latent representation space, without any assumption on the form of the treatment selection/assignment function.
Urban Structure, Subway Systemand Housing Price: Evidence from Beijing and Hangzhou, China
TL;DR: In this paper, the authors proposed a constrained clustering method to quantify the characteristics of urban structure, which can not only reveal the spatial heterogeneity of the housing market, but also provide a link between heterogeneity and the underlying urban structure.
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A mixed-integer programming strategy for liquid helium global supply chain planning
TL;DR: A large-scale, discrete time, path-based integer-programming model is developed which solves optimally with CPLEX, and results implementing a rolling horizon structure and testing based on historical data are presented.
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Adversarial balancing-based representation learning for causal effect inference with observational data
TL;DR: In this paper, a neural network framework called Adversarial balancing-based representation learning for Causal Effect Inference (ABCEI) is proposed to estimate the conditional average treatment effect (CATE) from observational data.
Estimating the long-term cost to serve new customers in joint distribution
TL;DR: This work analyzes the impacts of both routing and allocation models on cost to serve and constructs appropriate attributes for estimation based on geographical dispersion based on the relationship between multiple geographic factors and cost.
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