Luca Baldini

Orcid: 0000-0003-4391-2598

Affiliations:
  • University of Rome - La Sapienza, Department of Information Engineering, Electronics and Telecommunications, Italy


According to our database1, Luca Baldini authored at least 13 papers between 2019 and 2022.

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

Timeline

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Bibliography

2022
Evolutionary graph classification systems by granular computing based embedding.
PhD thesis, 2022

Intrusion Detection in Wi-Fi Networks by Modular and Optimized Ensemble of Classifiers: An Extended Analysis.
SN Comput. Sci., 2022

A Multi-objective Optimization Approach for the Synthesis of Granular Computing-Based Classification Systems in the Graph Domain.
SN Comput. Sci., 2022

A class-specific metric learning approach for graph embedding by information granulation.
Appl. Soft Comput., 2022

On Information Granulation via Data Clustering for Granular Computing-Based Pattern Recognition: A Graph Embedding Case Study.
Algorithms, 2022

2021
A Multi-agent Approach for Graph Classification.
Proceedings of the 13th International Joint Conference on Computational Intelligence, 2021

Relaxed Dissimilarity-based Symbolic Histogram Variants for Granular Graph Embedding.
Proceedings of the 13th International Joint Conference on Computational Intelligence, 2021

2020
Facing Big Data by an Agent-Based Multimodal Evolutionary Approach to Classification.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Exploiting Cliques for Granular Computing-based Graph Classification.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Intrusion Detection in Wi-Fi Networks by Modular and Optimized Ensemble of Classifiers.
Proceedings of the 12th International Joint Conference on Computational Intelligence, 2020

Complexity vs. Performance in Granular Embedding Spaces for Graph Classification.
Proceedings of the 12th International Joint Conference on Computational Intelligence, 2020

2019
Calibration Techniques for Binary Classification Problems: A Comparative Analysis.
Proceedings of the 11th International Joint Conference on Computational Intelligence, 2019

Stochastic Information Granules Extraction for Graph Embedding and Classification.
Proceedings of the 11th International Joint Conference on Computational Intelligence, 2019


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