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The appeals of quadratic majorization–minimization
Majorization–minimization (MM) is a versatile optimization technique that operates on surrogate functions satisfying tangency and domination...
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An inexact proximal majorization-minimization algorithm for remote sensing image stripe noise removal
The stripe noise existing in remote sensing images badly degrades the visual quality and restricts the precision of data analysis. Therefore, many...
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Majorization-minimization-based Levenberg–Marquardt method for constrained nonlinear least squares
A new Levenberg–Marquardt (LM) method for solving nonlinear least squares problems with convex constraints is described. Various versions of the LM...
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A majorization–minimization-based method for nonconvex inverse rig problems in facial animation: algorithm derivation
Automated methods for facial animation are a necessary tool in the modern industry since the standard blendshape head models consist of hundreds of...
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A Majorization-Minimization Algorithm for Optimal Sensor Location in Distributed Parameter Systems
The wide availability of effective and efficient convex optimization algorithms makes convex relaxation of optimum sensor location problems enjoy...
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Wideband MIMO Radar Transmit Beampattern Synthesis via Majorization–Minimization
We consider the design of constant-modulus waveforms for wideband multiple-input multiple-output radar. The aim is to match a desired transmit...
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Majorization–Minimization approach for real-time enhancement of sparsity-driven SAR imaging
The earlier works in the context of sparsity-driven SAR imaging have shown significant improvement in the reconstruction process due to admitting...
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Efficiency of higher-order algorithms for minimizing composite functions
Composite minimization involves a collection of functions which are aggregated in a nonsmooth manner. It covers, as a particular case, smooth...
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Multinomial Restricted Unfolding
For supervised classification we propose to use restricted multidimensional unfolding in a multinomial logistic framework. Where previous research...
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A new algorithm and a discussion about visualization for logistic reduced rank regression
Logistic reduced rank regression is a useful data analysis tool when we have multiple binary response variables and a set of predictors. In this...
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Advanced Techniques in Optimization for Machine Learning and Imaging
In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and...
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Majoration-Minimization for Sparse SVMs
Several decades ago, Support Vector Machines (SVMs) were introduced for performing binary classification tasks, under a supervised framework....
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Hybrid priors based on weighted hyper-Laplacian with overlapping group sparsity for poisson noise removal
Poisson noise widely exists in photo-limited imaging systems, which is very difficult to remove because of its signal-dependent and multiplicative...
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Infimal convolution and AM-GM majorized total variation-based integrated approach for biosignal denoising
Biomedical measurements are generally contaminated with substantial noise from various sources, including thermal noise, interference from other...
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A Local MM Subspace Method for Solving Constrained Variational Problems in Image Recovery
This article introduces a new penalized majorization–minimization subspace algorithm (P-MMS) for solving smooth, constrained optimization problems....
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Energy efficiency optimization for a RIS-assisted multi-cell communication system based on a practical RIS power consumption model
Reconfigurable intelligent surface (RIS) is widely accepted as a potential technology to assist in communication between base stations (BSs) and...
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Efficient seismic data reconstruction based on Geman function minimization
Seismic data typically contain random missing traces because of obstacles and economic restrictions, influencing subsequent processing and...
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Refining the time–frequency characteristic of non-stationary signal for improving time–frequency representation under variable speeds
Time–frequency ridge not only exhibits the variable process of non-stationary signal with time changing but also provides the information of signal...
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