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Quantile regression in high-dimension with breaking [PDF]
Journal of Statistical Theory and Applications (JSTA), 2013 The paper considers a linear regression model in high-dimension for which the predictive variables can change the influence on the response variable at unknown times (called change-points).
Gabriela Ciuperca
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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
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Ensemble Linear Subspace Analysis of High-Dimensional Data
Entropy, 2021 Regression models provide prediction frameworks for multivariate mutual information analysis that uses information concepts when choosing covariates (also called features) that are important for analysis and prediction.
S. Ejaz Ahmed, Saeid Amiri, Kjell Doksum
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Penalty methods for a variational quantum eigensolver
Physical Review Research, 2021 The variational quantum eigensolver (VQE) is a promising algorithm to compute eigenstates and eigenenergies of a given quantum system that can be performed on a near-term quantum computer.
Kohdai Kuroiwa, Yuya O. Nakagawa
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F1000Research, 2022 Gene expression data have been used to infer gene-gene networks (GGN) where an edge between two genes implies the conditional dependence of these two genes given all the other genes.
Wei Sun, Qian (Vicky) Wu, Li Hsu
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On two recent nonconvex penalties for regularization in machine learning
Results in Applied Mathematics, 2022 Regularization methods are often employed to reduce overfitting of machine learning models. Nonconvex penalty functions are often considered for regularization because of their near-unbiasedness properties.
Sujit Vettam, Majnu John
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The Multi-Objective Transportation Problem Solve with Geometric Mean and Penalty Methods
Indonesian Journal of Innovation and Applied Sciences, 2023 The traditional (classical) Transportation Problem (TP) can be viewed as a specific case of the Linear Programming (LP) problem, as well as its models are used to find the best solution for the problem of predetermined how many units of a good or service
K.P.O.Niluminda, E.M.U.S.B.Ekanayake
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工程科学学报, 2023 Material data are prepared in batches and stages, and data distribution in different batches varies. However, the average accuracy of neural networks declines when learning material data by batch, resulting in great challenges to the application of ...
Hong-ye WANG, Quan QIAN, Xing WU
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LASSO type penalized spline regression for binary data
BMC Medical Research Methodology, 2021 Background Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be used for smoothing by considering the knot coefficients from a regression spline as random effects.
Muhammad Abu Shadeque Mullah +2 more
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EURO Journal on Computational Optimization, 2022 This paper considers the problem of decentralized, personalized federated learning. For centralized personalized federated learning, a penalty that measures the deviation from the local model and its average, is often added to the objective function ...
Abdurakhmon Sadiev +7 more
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