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Black-Box and Data-Driven Computation

Rong Jin (), Weili Wu (), My T. Thai () and Ding-Zhu Du ()
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Rong Jin: University of Texas at Dallas
Weili Wu: University of Texas at Dallas
My T. Thai: University of Florida
Ding-Zhu Du: University of Texas at Dallas

A chapter in Black Box Optimization, Machine Learning, and No-Free Lunch Theorems, 2021, pp 163-168 from Springer

Abstract: Abstract Black box has been an important tool in studying computational complexity theory and has been used for establishing the hardness of problems. With an exponential growth in big data recently, data-driven computation has utilized black box as a tool for proving solutions to some computational problems. In this note, we present several observations on this new role of black box using reduction techniques in the computational complexity theory.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-66515-9_6

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DOI: 10.1007/978-3-030-66515-9_6

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