Jason J. Sauppe

University of Wisconsin–La Crosse — United States

Mathematics · Physical Sciences

10h-index741citations23works0.02yr avg
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Research Topics

Statistical Methods and Inference(8), Advanced Causal Inference Techniques(8), Vehicle Routing Optimization Methods(5), Statistical Methods and Bayesian Inference(3), Bayesian Modeling and Causal Inference(3)

Publications23 total

Results for the close-enough traveling salesman problem with a branch-and-bound algorithm
Computational Optimization and Applications·2023· 9 cited
Network flow methods for the minimum covariate imbalance problem
European Journal of Operational Research·2021· 6 cited
An Improved Branch-and-Bound Algorithm for the One-Machine Scheduling Problem with Delayed Precedence Constraints
INFORMS journal on computing·2020· 3 cited
Comparison of the number of nodes explored by cyclic best first search with depth contour and best first search
Computers & Operations Research·2020· 11 cited
Duality in balance optimization subset selection
Annals of Operations Research·2020· 1 cited
Jason J. Sauppe
Authors group·2019
Treatment Effect Decomposition and Bootstrap Hypothesis Testing in Observational Studies
Annals of Data Science·2018· 1 cited
Bias in Balance Optimization Subset Selection: Exploration through examples
Journal of the Operational Research Society·2018· 6 cited
The role of covariate balance in observational studies
Naval Research Logistics (NRL)·2017· 23 cited
Cyclic best first search: Using contours to guide branch‐and‐bound algorithms
Naval Research Logistics (NRL)·2017· 12 cited
Identifying NCAA tournament upsets using Balance Optimization Subset Selection
Journal of Quantitative Analysis in Sports·2017· 27 citedOpen Access
Targeted Marketing Using Balance Optimization Subset Selection
Annals of Data Science·2016
Branch-and-bound algorithms: A survey of recent advances in searching, branching, and pruning
Discrete Optimization·2016· 515 cited
Assigning Panels to Meeting Rooms at the National Science Foundation
INFORMS Journal on Applied Analytics·2015
Balance Optimization Subset Selection: A framework for causal inference with observational data
2015· 5 cited
Forecasting the 2012 and 2014 Elections Using Bayesian Prediction and Optimization
SAGE Open·2015· 2 citedOpen Access
A Wide Branching Strategy for the Graph Coloring Problem
INFORMS journal on computing·2014· 7 cited
Complexity and Approximation Results for the Balance Optimization Subset Selection Model for Causal Inference in Observational Studies
INFORMS journal on computing·2014· 19 cited
An algorithm to solve the proportional network flow problem
Optimization Letters·2013· 6 cited
Balance Optimization Subset Selection (BOSS): An Alternative Approach for Causal Inference with Observational Data
Operations Research·2013· 37 cited
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Frequent Co-authors

Sheldon H. Jacobson(20), David R. Morrison(7), Edward C. Sewell(7), Wenda Zhang(4), Hee Youn Kwon(3), Alexander Nikolaev(2), Wendy K. Tam Cho(2), Shouvik Dutta(2), Gio K Kao(1), Dorit S. Hochbaum(1), Xu Rao(1), Steven E. Rigdon(1)