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On estimation with weighted balanced-type loss function
Statistics & Probability Letters, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jozani, Mohammad Jafari +2 more
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LINEAR ESTIMATORS OF A POISSON MEAN UNDER BALANCED LOSS FUNCTIONS
Statistics & Risk Modeling, 1998Summary: This paper considers estimation of a Poisson mean using \textit{A. Zellner}'s [\textit{S.S. Gupta} et al. (eds.), Stat. Decision Theory Relat. Topics V. Proc. fifth Purdue Int. Symp., 377-390 (1994; Zbl 0787.62035)] balanced loss function \[ L_B(\lambda, \widehat\lambda) =(w/n) \sum^n_{i=1} (X_i-\widehat \lambda)^2+(1-w) (\lambda- \widehat ...
Chung, Younshik +2 more
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Balance-batch: An Optimized Method for Semantic Segmentation Loss Functions
2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL), 2020Class-imbalanced data easily generates under-fitting problems in deep neural networks, which seriously limits the performance of the network. Several schemes have been proposed to alleviate the class-imbalance, i.e., data augmentation and network structure optimization. Our work has two main contributions: First, we proposed an optimized method Balance-
Yifeng Huang, Zhirong Tang, Kaixiong Su
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Sensorimotor function and standing balance in older adults with transtibial limb loss
Clinical Biomechanics, 2023Limited research has focused on older prosthesis users despite the expected compounded effects of age and amputation on sensorimotor function, balance, and falls. This study compared sensorimotor factors and standing balance between older individuals with and without transtibial amputation, hypothesizing that prosthesis users would demonstrate worse ...
Matthew J, Major, Rebecca L, Stine
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IEEE Transactions on Neural Networks and Learning Systems, 2021
Imbalanced class distribution is an inherent problem in many real-world classification tasks where the minority class is the class of interest. Many conventional statistical and machine learning classification algorithms are subject to frequency bias ...
K. Ruwani +2 more
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Imbalanced class distribution is an inherent problem in many real-world classification tasks where the minority class is the class of interest. Many conventional statistical and machine learning classification algorithms are subject to frequency bias ...
K. Ruwani +2 more
semanticscholar +1 more source
Adaptive Spatial Location With Balanced Loss for Video Captioning
IEEE transactions on circuits and systems for video technology (Print), 2022Many pioneering approaches have verified the effectiveness of utilizing the global temporal and local object information for video understanding tasks and have achieved significant progress.
Linghui Li +5 more
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Gradient Analysis of Loss Function Based on System Balance
2020In recent years, deep learning has been widely used in various fields of social life. The theoretical understanding on how it works also makes people curious.
Suman Xia +3 more
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Estimation of a normal mean relative to balanced loss functions
Statistical Papers, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sanjari Farsipour, N., Asgharzadeh, A.
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Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets
European Conference on Computer Vision, 2020We present a new loss function called Distribution-Balanced Loss for the multi-label recognition problems that exhibit long-tailed class distributions.
Tong Wu +4 more
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Constrained Bayes and Empirical Bayes Estimation with Balanced Loss Functions
Communications in Statistics - Theory and Methods, 2007This article develops constrained Bayes and empirical Bayes estimators under balanced loss functions. In the normal-normal example, estimators of the mean squared errors of the EB and constrained EB estimators are provided which are correct asymptotically up to O(m −1), m denoting the number of strata.
Malay Ghosh, Myung Joon Kim, Dalho Kim
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