David Charte | DeepAI

DeepAI AI Chat

Featured Co-authors

Francisco Herrera
48 publications
Salvador García
18 publications
Francisco Charte
11 publications
María J. del Jesus
9 publications
Antonio J. Rivera
6 publications
Alberto Fernandez
4 publications
José Daniel Pascual-Triana
1 publication
Marta Andrés Arroyo
1 publication

∙ 11/11/2021

Reducing Data Complexity using Autoencoders with Class-informed Loss Functions

Available data in machine learning applications is becoming increasingly...

0 David Charte, et al. ∙

∙ 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...

13 José Daniel Pascual-Triana, et al. ∙

∙ 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...

40 David Charte, et al. ∙

∙ 05/08/2020

A Showcase of the Use of Autoencoders in Feature Learning Applications

Autoencoders are techniques for data representation learning based on ar...

0 David Charte, et al. ∙

∙ 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...

0 David Charte, et al. ∙

∙ 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 ...

0 Francisco Charte, et al. ∙

∙ 01/04/2018

A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines

Many of the existing machine learning algorithms, both supervised and un...

0 David Charte, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world