Eduardo Paluzo-Hidalgo

Orcid: 0000-0002-4280-5945

Affiliations:
  • Universidad de Sevilla, Spain


According to our database1, Eduardo Paluzo-Hidalgo authored at least 18 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
An In-Depth Analysis of Data Reduction Methods for Sustainable Deep Learning.
CoRR, 2024

SIMAP: A simplicial-map layer for neural networks.
CoRR, 2024

2023
A Survey of Vectorization Methods in Topological Data Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

A Topological Approach to Measuring Training Data Quality.
CoRR, 2023

Explainability in Simplicial Map Neural Networks.
CoRR, 2023

The Metric-aware Kernel-width Choice for LIME.
Proceedings of the Joint Proceedings of the xAI-2023 Late-breaking Work, 2023

2022
Topology-based representative datasets to reduce neural network training resources.
Neural Comput. Appl., 2022

Strong Euler well-composedness.
J. Comb. Optim., 2022

2021
Optimizing the Simplicial-Map Neural Network Architecture.
J. Imaging, 2021

Emotion recognition in talking-face videos using persistent entropy and neural networks.
CoRR, 2021

2020
Approximating lower-star persistence via 2D combinatorial map simplification.
Pattern Recognit. Lett., 2020

Two-hidden-layer feed-forward networks are universal approximators: A constructive approach.
Neural Networks, 2020

Euler Well-Composedness.
Proceedings of the Combinatorial Image Analysis - 20th International Workshop, 2020

2019
Towards a Philological Metric through a Topological Data Analysis Approach.
CoRR, 2019

Two-hidden-layer Feedforward Neural Networks are Universal Approximators: A Constructive Approach.
CoRR, 2019

Representative Datasets: The Perceptron Case.
CoRR, 2019

Towards Emotion Recognition: A Persistent Entropy Application.
Proceedings of the Computational Topology in Image Context - 7th International Workshop, 2019

2018
Representative datasets for neural networks.
Electron. Notes Discret. Math., 2018


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