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Robust Loss Functions for Boosting
Neural Computation, 2007Boosting is known as a gradient descent algorithm over loss functions. It is often pointed out that the typical boosting algorithm, Adaboost, is highly affected by outliers. In this letter, loss functions for robust boosting are studied. Based on the concept of robust statistics, we propose a transformation of loss functions that makes boosting ...
Kanamori, Takafumi +3 more
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Physiologic functional imaging in “functional” visual loss
Survey of Ophthalmology, 1996Neuroimaging with nuclear medicine techniques permits assessment of brain function by measurement of metabolism or blood flow. Such studies complement the anatomic information derived from computed tomography (CT) or magnetic resonance imaging (MRI).
Jonathan Wirtschafter +3 more
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Loss functions for Loss Given Default model comparison
European Journal of Operational Research, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hurlin, Christophe +2 more
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A novel loss function of deep learning in wind speed forecasting
, 2022Xi Chen +9 more
semanticscholar +1 more source
ILF-LSTM: enhanced loss function in LSTM to predict the sea surface temperature
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2022B. Usharani
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Laminin: loss-of-function studies
Cellular and Molecular Life Sciences, 2016Laminin, one of the most widely expressed extracellular matrix proteins, exerts many important functions in multiple organs/systems and at various developmental stages. Although its critical roles in embryonic development have been demonstrated, laminin's functions at later stages remain largely unknown, mainly due to its intrinsic complexity and lack ...
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Person Re-identification by Multi-Channel Parts-Based CNN with Improved Triplet Loss Function
Computer Vision and Pattern Recognition, 2016De Cheng +4 more
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