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A parallel method for large scale convex regression problems
Necdet S. Aybat
, Zi Wang
Harold and Inge Marcus Department of Industrial and Manufacturing Engineering
Research output
:
Chapter in Book/Report/Conference proceeding
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Conference contribution
10
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Scopus citations
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Dive into the research topics of 'A parallel method for large scale convex regression problems'. Together they form a unique fingerprint.
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Mathematics
Least Square
100%
Observed Data
100%
Convex Function
100%
Square Estimator
100%
Quadratic Programming
100%
Finite Number
50%
Data Point
50%
Operations Research
50%
Interior Point
50%
Parallelization
50%
Piecewise Linear
50%
Keyphrases
Regression Problem
100%
Parallel Methods
100%
Convex Function
66%
Least Squares Estimator
66%
Quadratic Program
66%
Finite number
33%
Electrical Engineering
33%
Piecewise Linear
33%
Operations Research
33%
Memory Consumption
33%
Parallelization
33%
Interior Point Method
33%
First-order Methods
33%
Program Formulation
33%
Economic Operation
33%
Engineering
Observed Data
100%
Least Square
100%
Parallel Method
100%
Data Point
50%
Finite Number
50%
Electrical Engineering
50%
Point Method
50%
Interior Point
50%
Computer Science
Convex Function
100%
Least Squares Method
100%
Regression Problem
100%
System Analysis
50%
Parallelization
50%
Interior-Point Method
50%
Operations Research
50%
Piecewise Linear
50%