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11/11/2021
Reducing Data Complexity using Autoencoders with Class-informed Loss Functions
Available data in machine learning applications is becoming increasingly...
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07/15/2020
Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect
Data Science and Machine Learning have become fundamental assets for com...
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05/21/2020
An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges
In many machine learning tasks, learning a good representation of the da...
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05/08/2020
A Showcase of the Use of Autoencoders in Feature Learning Applications
Autoencoders are techniques for data representation learning based on ar...
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11/29/2018
A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods
Machine learning is a field which studies how machines can alter and ada...
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02/10/2018
Tips, guidelines and tools for managing multi-label datasets: the mldr.datasets R package and the Cometa data repository
New proposals in the field of multi-label learning algorithms have been ...
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01/04/2018
