Results 281 to 290 of about 28,744 (310)
Some of the next articles are maybe not open access.
Robust graph learning via constrained elastic-net regularization
Neurocomputing, 2016Graph has been widely researched for characterizing data structure and successfully applied in many fields. To date, one popular kind of graph constructing methods is based on linear reconstruction coefficients. However, it is still a challenge to make the graph maintain the intra-class relations and diminish the inter-class relations.
Bo Liu, Liping Jing, Jian Yu, Jia Li
openaire +1 more source
Elastic net regularized dictionary learning for image classification
Multimedia Tools and Applications, 2014Dictionary learning plays a key role in image representation for classification. A multi-modal dictionary is usually learned from feature samples across different classes and shared in the feature encoding process. Ideally each atom in dictionary corresponds to a single class of images, while each class of images corresponds to a certain group of atoms.
Bin Shen, Bao-Di Liu, Qifan Wang
openaire +1 more source
Low-rank elastic-net regularized multivariate Huber regression model
Applied Mathematical Modelling, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chen, Bingzhen +2 more
openaire +1 more source
Multivariate Curve Resolution with Elastic Net Regularization
2011The purpose of Multivariate Curve Resolution (MCR) is to recover the concentration profile and the source spectra without any prior knowledge. We hypothesis that each source is characterized by a linear superposition of Gaussian peaks of fixed spread. Multivariate curve resolution–alternating least squares (MCR-ALS) is a Conventional MCR method.
Zhu Xin-feng, Wang Jian-dong, Li Bin
openaire +1 more source
Kernelized Elastic Net Regularization based on Markov selective sampling
Knowledge-Based Systems, 2019Abstract This paper extends Kernelized Elastic Net Regularization (KENReg) algorithm from the assumption of independent and identically distributed (i.i.d.) samples to the case of non-i.i.d. samples. We first establish the generalization bounds of KENReg algorithm with uniformly ergodic Markov chain samples, then we prove that the KENReg algorithm ...
Bin Zou, Huidong jin, Jie Xu
exaly +2 more sources
Distributed regularized stochastic configuration networks via the elastic net
Neural Computing and Applications, 2020Stochastic configuration network (SCN) has great potential in developing fast learning model with sound generalization capability and can be easily extended to the distributed computing framework. This paper aims to develop a distributed regularized stochastic configuration network to solve the limitations of traditional centralized learning on the ...
Lijie Zhao +3 more
openaire +1 more source
Elastic Net Regularized Dictionary Learning for Face Recognition
2018The sparse representation based classification (SRC) method and collaborative representation based classification (CRC) method attract more and more attention in recent years, due to their promising result and robustness for face recognition. However, both SRC and CRC algorithms directly use the training samples as the dictionary, which leads to large ...
Li Wang, Yan-Jiang Wang, Bao-Di Liu
openaire +1 more source
Elastic Net Regularized Logistic Regression Using Cubic Majorization
2014 22nd International Conference on Pattern Recognition, 2014In this work, a coordinate solver for elastic net regularized logistic regression is proposed. In particular, a method based on majorization maximization using a cubic function is derived. This to reliably and accurately optimize the objective function at each step without resorting to line search.
openaire +1 more source
Elastic net-regularized latent factor model for recommender systems
2018 IEEE 15th International Conference on Networking, Sensing and Control (ICNSC), 2018Latent factor (LF) models are highly efficient in recommender systems. The problem of LF analysis is defined on high-dimensional and sparse (HiDS) matrices corresponding to relationships among numerous entities in industrial applications. It is ill-posed without a unique and optimal solution.
Xi Cheng, Xin Luo
openaire +1 more source
Fast Source Reconstruction via ADMM with Elastic Net Regularization
2018 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting, 2018Norm-1 regularized optimization algorithms are commonly used for Compressive Sensing applications. In this paper, an optimization algorithm based on the Alternating Direction Method of Multipliers (ADMM) together with the Elastic Net regularization is presented.
Juan Heredia-Juesas +2 more
openaire +1 more source