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This paper analyzes a popular loss function used in machine learning called the log-cosh loss function.
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Chernozhukov, V. and Fernandez-Val, I. and Galichon, A., “ Quantile and probability curves without crossing”, Econometrica 78, 1093-1125, 2010
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Hettmansperger, T. P., McKean, J. W., “Robust Nonparametric Statistical Methods”, 2nd Ed. Chapman Hall, New York, 2011
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Chen P., Chen G., Zhang S. “Log Hyperbolic Cosine Loss Improves Variational Auto-Encoder”, submitted to Sixth International Conference on Learning Representations, openreview.net, 2018
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Amerise, I., “Quantile Regression Estimation Using Non-Crossing Constraints”, Journal of Mathematics and Statistics, Volume 14: 107-118, 2018
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Grover, P. (2019, September 25). “5 Regression Loss Functions All Machine Learners Should Know”. Retrieved from https://heartbeat.fritz.ai/5-regression-loss-functions-all-machine-learners-should-know-4fb140e9d4b0
Jadon, S. “A survey of loss functions for semantic segmentation”, arXiv:2006.14822v4, Sept. 2020
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He, X., Pan, X., Tan, K. M., and Zhou, W., “Smoothed Quantile Regression with Large-Scale Inference”, arXiv:202.05187v1, 2020
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X. Xu, J. Li, Y. Yang and F. Shen, ”Toward Effective Intrusion Detection Using Log-Cosh Conditional Variational Autoencoder,” in IEEE Internet of Things Journal, vol. 8, no. 8, pp. 6187-6196, April 2021
2021
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Kalifi, E. Y. et. al, “Classification of Breast Cancer Lesions in Ultrasound Images by Using Attention Layer and Loss Ensemble in Deep Convolutional Neural Networks,” National Library of Medicine, published online Oct. 2021
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2019
Cited alongside, same era.
2019
Cited alongside, same era.
Wang, Q. et. al, “A Comprehensive Survey of Loss Functions in Machine Learning”, Annals of Data Science 9, April 2020
2020
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R software, limma
Cited in the paper.
numpy documentation, https://numpy.org/doc
Cited in the paper.
TensorFlow documentation regarding log-cosh loss, Retrieved from https://www.tensorflow.org/api-docs/python/tf/keras/losses/log-cosh
Cited in the paper.
PyTorch documentation, https://pytorch.org/doc
Cited in the paper.
2021
Later among the works it cites.
Gupta,S. (2022, April 14). “The 7 Most Common Machine Learning Loss Functions”. Retrieved from https://builtin.com/machine-learning/common-loss-functions
2022
Closest in time.
Saleh, A.K.Md.E. et. al, “Rank-based Shrinkage and Selection with Application to Machine Learning”, John Wiley and Sons Publishers, Feb. 2022
2022
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