Some results on quadratic credibility premium using the balanced loss function [PDF]
Arab Journal of Mathematical Sciences, 2023 Purpose – This paper generalizes the quadratic framework introduced by Le Courtois (2016) and Sumpf (2018), to obtain new credibility premiums in the balanced case, i.e. under the balanced squared error loss function.
Farouk Metiri +2 more
doaj +3 more sources
Balanced Loss Function for Accurate Surface Defect Segmentation
Applied Sciences, 2023 The accurate image segmentation of surface defects is challenging for modern convolutional neural networks (CNN)-based segmentation models. This paper identifies that loss imbalance is a critical problem in segmentation accuracy improvement.
Zhouyang Xie +4 more
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Stein-Rule Estimation under an Extended Balanced Loss Function [PDF]
Journal of Statistical Computation and Simulation, 2007 This paper extends the balanced loss function to a more general set up. The ordinary least squares and Stein-rule estimators are exposed to this general loss function with quadratic loss structure in a linear regression model.
---, Shalabh +2 more
core +2 more sources
Balanced-BiEGCN: A Bidirectional EvolveGCN with a Class-Balanced Learning Network for Dynamic Anomaly Detection in Bitcoin [PDF]
EntropyBitcoin transaction anomaly detection is essential for maintaining financial market stability. A significant challenge is capturing the dynamically evolving transaction patterns within transaction networks.
Bo Xiao, Wei Yin
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Breakpoint-resolved balanced t(2;12)(q35;q24.31) disrupting HNF1A in multigenerational MODY-3: Diagnostic utility of long-read genome sequencing and therapeutic impact [PDF]
Metabolism OpenBalanced translocations that interrupt HNF1A are seldom documented in MODY-3. We studied a three-generation family with early-onset, non-autoimmune diabetes consistent with MODY-3.
Pamela Rivero-García +9 more
doaj +2 more sources
IoU-Balanced loss functions for single-stage object detection [PDF]
Pattern Recognition Letters, 2022 Single-stage object detectors have been widely applied in computer vision applications due to their high efficiency. However, we find that the loss functions adopted by single-stage object detectors hurt the localization accuracy seriously. Firstly, the standard cross-entropy loss for classification is independent of the localization task and drives ...
Wu, Shengkai +3 more
openaire +2 more sources
On shrinkage estimation for balanced loss functions [PDF]
Journal of Multivariate Analysis, 2020 15 ...
Marchand, Éric, Strawderman, William E.
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Complexity, 2021 Majority research studies in the literature determine the weighted coefficients of balanced loss function by suggesting some arbitrary values and then conducting comparison study to choose the best.
Fuad S. Al-Duais, Mohammed Alhagyan
doaj +1 more source
Estimating Two Parameters of Lomax Distribution by Using the Upper Recorded Values under Two Balanced Loss Functions [PDF]
المجلة العراقية للعلوم الاحصائية, 2019 In this paper, two lomax distribution parameters are estimated along with the estimation of the reliability function under two balanced loss functions: the balanced squared error function and balanced linex loss function.
Enas Ghanem Abd alkader, Ray Al-Rassam
doaj +1 more source
Comparison of Risk Ratios of Shrinkage Estimators in High Dimensions
Mathematics, 2021 In this paper, we analyze the risk ratios of several shrinkage estimators using a balanced loss function. The James–Stein estimator is one of a group of shrinkage estimators that has been proposed in the existing literature.
Abdenour Hamdaoui +3 more
doaj +1 more source