MM for penalized estimation
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DOI: 10.1007/s11749-021-00770-2
Abstract: Penalized estimation can conduct variable selection and parameter estimation simultaneously. The general framework is to minimize a loss function subject to a penalty designed to generate sparse variable selection. The majorization–minimization (MM) algorithm is a… read more here.
Keywords: estimation; loss functions; penalized estimation; nonconvex loss ... See more keywords
Three-way Decision Models of Cognitive Computing in Pythagorean Fuzzy Environments
Sign Up to like & getrecommendations! Published in 2021 at "Cognitive Computation"
DOI: 10.1007/s12559-021-09867-0
Abstract: Loss functions, commonly believed to be the cost of cognitive computing, are a key element in decision-making, and three-way decisions can be regarded as a cognitive computing method that seeks to minimize the overall risks… read more here.
Keywords: decision models; way decision; loss functions; decision ... See more keywords
Comparing loss functions and interval estimates for survival data
Sign Up to like & getrecommendations! Published in 2020 at "Ecological Modelling"
DOI: 10.1016/j.ecolmodel.2020.109077
Abstract: Abstract We compare parameter point and interval estimates based on the symmetric bounded loss function, as used in the Add-my-Pet collection on animal energetics, with the maximum likelihood method for number of surviving individuals as… read more here.
Keywords: comparing loss; interval estimates; maximum likelihood; loss function ... See more keywords
Nonparametric tests for Optimal Predictive Ability
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DOI: 10.1016/j.ijforecast.2020.10.002
Abstract: Abstract A nonparametric method for comparing multiple forecast models is developed and implemented. The hypothesis of Optimal Predictive Ability generalizes the Superior Predictive Ability hypothesis from a single given loss function to an entire class… read more here.
Keywords: optimal predictive; predictive ability; loss functions; hypothesis ... See more keywords
Structure formation, optical properties and energy loss functions of meso-tetraphenylporphyrin manganese(III) chloride complex thin films for energy conversion applications
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DOI: 10.1016/j.optmat.2020.110663
Abstract: Abstract Thin films of meso-tetraphenylporphyrin manganese chloride complex (MnClTPP) have been prepared by evacuated thermal evaporation technique. The structure formation of MnClTPP films has been identified using atomic force microscopy and X-ray diffraction techniques. The… read more here.
Keywords: energy; energy loss; structure; loss functions ... See more keywords
Multivariate asymmetric loss functions of the European Central Bank
Sign Up to like & getrecommendations! Published in 2020 at "Applied Economics Letters"
DOI: 10.1080/13504851.2020.1795067
Abstract: ABSTRACT This study investigates asymmetric loss functions in the forecasts of real output growth and inflation published by the European Central Bank (ECB). In contrast to previous studies that examined each variable independently, this study… read more here.
Keywords: asymmetric loss; central bank; multivariate asymmetric; loss functions ... See more keywords
Bayesian Framework for Updating Seismic Loss Functions with Limited Observational Data in Low-to-Moderate Seismicity Regions
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Earthquake Engineering"
DOI: 10.1080/13632469.2021.1987356
Abstract: In low-to-moderate seismicity regions, seismic loss functions (SLFs) are barely established due to limited observational data, making it difficult to derive decision-making on disaster prevention a... read more here.
Keywords: moderate seismicity; seismicity regions; low moderate; seismic loss ... See more keywords
Asymmetric Loss Functions for Noise-Tolerant Learning: Theory and Applications.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3236459
Abstract: Supervised deep learning has achieved tremendous success in many computer vision tasks, which however is prone to overfit noisy labels. To mitigate the undesirable influence of noisy labels, robust loss functions offer a feasible approach… read more here.
Keywords: mml mml; mml; loss functions; noise tolerant ... See more keywords
Inference on P(X < Y) in Bivariate Lomax model based on progressive type II censoring
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DOI: 10.1371/journal.pone.0267981
Abstract: This article considers the estimation of the stress-strength reliability parameter, θ = P(X < Y), when both the stress (X) and the strength (Y) are dependent random variables from a Bivariate Lomax distribution based on… read more here.
Keywords: based progressive; progressive type; bivariate lomax; bayes estimators ... See more keywords
Correcting systematic errors by hybrid 2D correlation loss functions in nonlinear inverse modelling
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DOI: 10.1371/journal.pone.0284723
Abstract: Recently a new family of loss functions called smart error sums has been suggested. These loss functions account for correlations within experimental data and force modeled data to obey these correlations. As a result, multiplicative… read more here.
Keywords: smart error; methodology; systematic errors; loss ... See more keywords
Generation and Evaluation of Synthetic Computed Tomography (CT) from Cone-Beam CT (CBCT) by Incorporating Feature-Driven Loss into Intensity-Based Loss Functions in Deep Convolutional Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "Cancers"
DOI: 10.3390/cancers14184534
Abstract: Simple Summary Despite numerous benefits of cone-beam computed tomography (CBCT), its applications to radiotherapy were limited mainly due to degraded image quality. Recently, enhancing the CBCT image quality by generating synthetic CT image by deep… read more here.
Keywords: network; similarity; loss; loss functions ... See more keywords