On Computing with Some Convex Relaxations for the Maximum-Entropy Sampling Problem
Published in INFORMS Journal on Computing, 35(2), 2023: 368-385, 2023
This paper provides a comprehensive computational study of various convex relaxations for the maximum-entropy sampling problem, analyzing their effectiveness and efficiency.
Recommended citation: Zhongzhu Chen, Marcia Fampa, and Jon Lee. (2023). "On Computing with Some Convex Relaxations for the Maximum-Entropy Sampling Problem." INFORMS Journal on Computing, 35(2), 368-385.
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