Robust weighted Gaussian processes
This paper presents robust weighted variants of batch and online standard Gaussian processes (GPs) to effectively reduce the negative impact of outliers in the corresponding GP models. This is done by introducing robust data weighers that rely on robust and quasi-robust weight functions that come fr...
Saved in:
Main Author: | Mederos, Boris |
---|---|
Other Authors: | Ramirez-Padron, Ruben, González, Avelino J. |
Format: | Artículo |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://doi.org/10.1007/s00180-020-01011-0 https://link.springer.com/article/10.1007/s00180-020-01011-0 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Application of IoT with haptics interface in the smart manufacturing industry
by: Contreras Masse, Roberto
Published: (2019) -
A Proposal for Data Breach Detection in Organizations Based on User Behavior
Published: (2021) -
Balancing estimation in rigid rotors based on machine learning: 7CP24-4
by: Ing. Juan Ángel Martínez Ramírez, et al.
Published: (2024) -
Inventory management for products with a sale single period and stochastic demand using Machine Learning models: 4CP22-16
by: Sergio Joaquín González Herrera, et al.
Published: (2022) -
Prototipo de redes neuronales para predecir posibles complicaciones por diabetes.
by: Puente Rodríguez, Fernando
Published: (2020)