Multi-Agent Estimation and Filtering for Minimizing Team Mean-Squared Error [PDF]
IEEE Transactions on Signal Processing, 2021 Motivated by estimation problems arising in autonomous vehicles and decentralized control of unmanned aerial vehicles, we consider multi-agent estimation and filtering problems in which multiple agents generate state estimates based on decentralized ...
Mohammad Afshari, Aditya Mahajan
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Mean Squared Error, Deconstructed [PDF]
Journal of Advances in Modeling Earth Systems, 2021 AbstractAs science becomes increasingly cross‐disciplinary and scientific models become increasingly cross‐coupled, standardized practices of model evaluation are more important than ever. For normally distributed data, mean squared error (MSE) is ideal as an objective measure of model performance, but it gives little insight into what aspects of model
Timothy O. Hodson +2 more
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Grid Search for Lowest Root Mean Squared Error in Predicting Optimal Sensor Location in Protected Cultivation Systems [PDF]
Frontiers in Plant Science, 2022 Irregular changes in the internal climates of protected cultivation systems can prevent attainment of optimal yield when the environmental conditions are not adequately monitored and controlled.
Daniel Dooyum Uyeh +12 more
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Mean Squared Error Representative Points of Pareto Distributions and Their Estimation [PDF]
EntropyPareto distributions are widely applied in various fields, such as economics, finance, and environmental studies. The modeling of real-world data has created a demand for the discretization of Pareto distributions.
Xinyang Li, Xiaoling Peng
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Exact Mean Integrated Squared Error
The Annals of Statistics, 1992 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Marron, J. S., Wand, M. P.
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Ensemble Averaging and Mean Squared Error
Journal of Climate, 2016 Abstract In fields such as climate science, it is common to compile an ensemble of different simulators for the same underlying process. It is a striking observation that the ensemble mean often outperforms at least half of the ensemble members in mean squared error (measured with respect to observations). In fact, as demonstrated in the
J. Rougier
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Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in estimating the mean squared error of the least squares estimator in linear regression. [PDF]
PLoS OneStolte M +6 more
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Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation [PDF]
International Joint Conference on Artificial Intelligence, 2021 Knowledge distillation (KD), transferring knowledge from a cumbersome teacher model to a lightweight student model, has been investigated to design efficient neural architectures.
Taehyeon Kim +4 more
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Optimizing LSTM Models for EUR/USD Prediction in the context of reducing energy consumption: An Analysis of Mean Squared Error, Mean Absolute Error and R-Squared [PDF]
E3S Web of Conferences, 2023 The purpose of this study was to develop and evaluate a Long Short-Term Memory (LSTM) model for Forex prediction. The data used was reprocessed and the LSTM model was developed and trained using a supervised learning approach with popular deep learning ...
Echrigui Rania, Hamiche Mhamed
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Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not
Geoscientific Model Development, 2022 . The root-mean-squared error (RMSE) and mean absolute error (MAE) are widely used metrics for evaluating models. Yet, there remains enduring confusion over their use, such that a standard practice is to present both, leaving it to the reader to decide ...
T. Hodson
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