Results 11 to 20 of about 12,040 (299)
Inertial proximal alternating minimization for nonconvex and nonsmooth problems [PDF]
Journal of Inequalities and Applications, 2017 In this paper, we study the minimization problem of the type L ( x , y ) = f ( x ) + R ( x , y ) + g ( y ) $L(x,y)=f(x)+R(x,y)+g(y)$ , where f and g are both nonconvex nonsmooth functions, and R is a smooth function we can choose.
Yaxuan Zhang, Songnian He
doaj +4 more sources
On accelerated alternating minimization [PDF]
, 2020 Alternating minimization (AM) optimization algorithms have been known for a long time and are of importance in machine learning problems, among which we are mostly motivated by approximating optimal transport distances. AM algorithms assume that the decision variable is divided into several blocks and minimization in each block can be done explicitly ...
Guminov, Sergey +2 more
core +4 more sources
EURO Journal on Computational Optimization, 2016 We analyze the proximal alternating linearized minimization algorithm (PALM) for solving non-smooth convex minimization problems where the objective function is a sum of a smooth convex function and block separable non-smooth extended real-valued convex ...
Ron Shefi, Marc Teboulle
exaly +3 more sources
Factor Analysis and Alternating Minimization [PDF]
, 2007 In this paper we make a first attempt at understanding how to build an optimal approximate normal factor analysis model. The criterion we have chosen to evaluate the distance between different models is the I-divergence between the corresponding normal laws.
Finesso L, Spreij P
openaire +5 more sources
Alternating minimization for regression with tropical rational functions
Algebraic Statistics, 2023 We propose an alternating minimization heuristic for regression over the space of tropical rational functions with fixed exponents. The method alternates between fitting the numerator and denominator terms via tropical polynomial regression, which is known to admit a closed form solution.
Alex Dunbar, Lars Ruthotto
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High-Resolution and Robust One-Bit Direct-of-Arrival Estimation via Reweighted Atomic Norm Estimation [PDF]
SensorsIn recent years, one-bit quantization has attracted widespread attention in the field of direction-of-arrival (DOA) estimation as a low-cost and low-power solution.
Rui Li +5 more
doaj +2 more sources
NON-CONVEX HYBRID TOTAL VARIATION FOR RESTORING MEDICAL IMAGE CORRUPTED BY POISSON NOISE [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 In this work, we proposed the hybrid non-convex regularizers for Poisson noise removal on medical images. The model is built by a combination of non-convex total variation and non-convex fractional total variation.
T. T. T. Tran +5 more
doaj +1 more source
Alternating minimization methods for strongly convex optimization [PDF]
, 2020 We consider alternating minimization procedures for convex optimization problems with variable divided in many block, each block being amenable for minimization with respect to its variable with freezed other variables blocks.
Dvurechensky, Pavel +3 more
core +3 more sources
Hybrid Precoding Algorithm for High Spectral Efficiency in mm-Wave MIMO Systems
Guangtongxin yanjiu, 2022 In mm-wave massive Multiple Input Multiple Output (MIMO) systems, in order to further improve the spectral efficiency of hybrid precoding in fully connected structure, an Alternate Minimization based on Gradient Descent (GD-AltMin) hybrid precoding ...
Wei ZHOU, Qiu-yan YANG
doaj +3 more sources
IEEE Access, 2022 Millimeter-wave (mm-wave) communication is the spectral frontier to meet the anticipated significant volume of high data traffic processing in next-generation systems.
Adeb Salh +7 more
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