Global optimization on non-convex two-way interaction truncated linear multivariate adaptive regression splines using mixed integer quadratic programming
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Publication:6118891
DOI10.1016/j.ins.2022.03.041OpenAlexW4220892699MaRDI QIDQ6118891
Jay M. Rosenberger, Feng Liu, Victoria C. P. Chen, Xinglong Ju
Publication date: 28 February 2024
Published in: Information Sciences (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.ins.2022.03.041
global optimizationgenetic algorithmmixed integer quadratic programmingmultivariate adaptive regression splinesgradient descent algorithm
Cites Work
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- GLOMIQO: global mixed-integer quadratic optimizer
- Numerical solution of systems of second-order boundary value problems using continuous genetic algorithm
- Double regularization methods for robust feature selection and SVM classification via DC programming
- Multivariate adaptive regression splines
- Global optimization of mixed-integer quadratically-constrained quadratic programs (MIQCQP) through piecewise-linear and edge-concave relaxations
- GGA: a modified genetic algorithm with gradient-based local search for solving constrained optimization problems
- A problem-specific non-dominated sorting genetic algorithm for supervised feature selection
- Evolutionary algorithm and multifactorial evolutionary algorithm on clustered shortest-path tree problem
- A multi-stage evolutionary algorithm for multi-objective optimization with complex constraints
- Global optimization of non-convex piecewise linear regression splines
- Approximate Dynamic Programming
- A Simplex Method for Function Minimization
- The Monte Carlo Method
- Introduction to global optimization.
- Experimental evaluation of heuristic optimization algorithms: A tutorial
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