Density-Based Penalty Parameter Optimization on C-SVM [PDF]
The Scientific World Journal, 2014 The support vector machine (SVM) is one of the most widely used approaches for data classification and regression. SVM achieves the largest distance between the positive and negative support vectors, which neglects the remote instances away from the SVM ...
Yun Liu +3 more
doaj +5 more sources
On the Adaptive Penalty Parameter Selection in ADMM
Algorithms, 2023 Many data analysis problems can be modeled as a constrained optimization problem characterized by nonsmooth functionals, often because of the presence of ℓ1-regularization terms.
Serena Crisci +2 more
doaj +3 more sources
An Adaptive Multiparameter Penalty Selection Method for Multiconstraint and Multiblock ADMM [PDF]
IEEE Open Journal of Signal ProcessingThis work presents a new method for online selection of multiple penalty parameters for the alternating direction method of multipliers (ADMM) algorithm applied to optimization problems with multiple constraints or functions with block matrix components.
Luke Lozenski +2 more
doaj +2 more sources
A permutation approach for selecting the penalty parameter in penalized model selection. [PDF]
Biometrics, 2015 Summary We describe a simple, computationally efficient, permutation-based procedure for selecting the penalty parameter in LASSO-penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of
Sabourin JA, Valdar W, Nobel AB.
europepmc +5 more sources
Automatic decrease of the penalty parameter in exact penalty function methods [PDF]
European Journal of Operational Research, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Annick Sartenaer
exaly +5 more sources
Generalized Quadratic Augmented Lagrangian Methods with Nonmonotone Penalty Parameters
Journal of Applied Mathematics, 2012 For nonconvex optimization problem with both equality and inequality constraints, we introduce a new augmented Lagrangian function and propose the corresponding multiplier algorithm. New iterative strategy on penalty parameter is presented.
Xunzhi Zhu +3 more
doaj +3 more sources
Robust and Simple ADMM Penalty Parameter Selection
IEEE Open Journal of Signal ProcessingWe present a new method for online selection of the penalty parameter for the alternating direction method of multipliers (ADMM) algorithm. ADMM is a widely used method for solving a range of optimization problems, including those that arise in signal ...
MICHAEL T. MCCANN, Brendt Wohlberg
doaj +2 more sources
QUBO Formulations and Characterization of Penalty Parameters for the Multi-Knapsack Problem
IEEE AccessThe Multi-Knapsack Problem (MKP) is a fundamental challenge in operations research and combinatorial optimization. Quantum computing introduces new possibilities for solving MKP using Quadratic Unconstrained Binary Optimization (QUBO) models.
Evren Guney +2 more
doaj +2 more sources
Image Classification and Land Cover Mapping Using Sentinel-2 Imagery: Optimization of SVM Parameters
Land, 2022 Land use/cover (LU/LC) classification provides proxies of the natural and social processes related to urban development, providing stakeholders with crucial information.
Saleh Yousefi +7 more
doaj +1 more source
Exact penalty functions with multidimensional penalty parameter and adaptive penalty updates [PDF]
Optimization Letters, 2021 In the second version, a number of small mistakes found in the paper was ...
openaire +2 more sources