M. Victoria Luzón

1.4k total citations
34 papers, 888 citations indexed

About

M. Victoria Luzón is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, M. Victoria Luzón has authored 34 papers receiving a total of 888 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 7 papers in Computer Networks and Communications and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in M. Victoria Luzón's work include Privacy-Preserving Technologies in Data (8 papers), Constraint Satisfaction and Optimization (7 papers) and Sentiment Analysis and Opinion Mining (6 papers). M. Victoria Luzón is often cited by papers focused on Privacy-Preserving Technologies in Data (8 papers), Constraint Satisfaction and Optimization (7 papers) and Sentiment Analysis and Opinion Mining (6 papers). M. Victoria Luzón collaborates with scholars based in Spain, Singapore and Netherlands. M. Victoria Luzón's co-authors include Francisco Herrera, Ana Valdivia, Eugenio Martínez‐Cámara, Nuria Rodríguez-Barroso, Erik Cambria, Francisco Ortín, Francisco Javier Melero, Robert Joan‐Arinyo, Enrique Yeguas-Bolívar and Iti Chaturvedi and has published in prestigious journals such as Expert Systems with Applications, Information Sciences and Neurocomputing.

In The Last Decade

M. Victoria Luzón

33 papers receiving 849 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
M. Victoria Luzón Spain 16 590 163 110 84 81 34 888
Bin Tan United States 10 441 0.7× 52 0.3× 681 6.2× 199 2.4× 26 0.3× 23 1.1k
Jagan Sankaranarayanan United States 18 504 0.9× 128 0.8× 529 4.8× 316 3.8× 13 0.2× 50 1.9k
Bob Price United States 12 315 0.5× 54 0.3× 246 2.2× 242 2.9× 4 0.0× 33 768
Mohamed Aly United States 13 659 1.1× 83 0.5× 345 3.1× 269 3.2× 8 0.1× 28 1.1k
Giuseppe D’Aniello Italy 17 363 0.6× 111 0.7× 152 1.4× 133 1.6× 18 0.2× 64 806
William I. Grosky United States 17 300 0.5× 53 0.3× 145 1.3× 733 8.7× 14 0.2× 115 1.2k
Vincenzo Deufemia Italy 20 458 0.8× 47 0.3× 516 4.7× 176 2.1× 23 0.3× 92 975
Manos Papagelis Canada 12 250 0.4× 52 0.3× 194 1.8× 101 1.2× 24 0.3× 46 726
Dominik Sacha Germany 13 402 0.7× 67 0.4× 56 0.5× 757 9.0× 5 0.1× 27 1.1k
Neil Y. Yen Japan 16 232 0.4× 72 0.4× 148 1.3× 91 1.1× 3 0.0× 77 682

Countries citing papers authored by M. Victoria Luzón

Since Specialization
Citations

This map shows the geographic impact of M. Victoria Luzón's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by M. Victoria Luzón with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Victoria Luzón more than expected).

Fields of papers citing papers by M. Victoria Luzón

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Victoria Luzón. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by M. Victoria Luzón. The network helps show where M. Victoria Luzón may publish in the future.

Co-authorship network of co-authors of M. Victoria Luzón

This figure shows the co-authorship network connecting the top 25 collaborators of M. Victoria Luzón. A scholar is included among the top collaborators of M. Victoria Luzón based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M. Victoria Luzón. M. Victoria Luzón is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rodríguez-Barroso, Nuria, et al.. (2025). Improving ( α , f ) -Byzantine resilience in federated learning via layerwise aggregation and cosine distance. Knowledge-Based Systems. 326. 114004–114004.
2.
Luzón, M. Victoria, Nuria Rodríguez-Barroso, Jose M. Moyano, et al.. (2024). A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends. IEEE/CAA Journal of Automatica Sinica. 11(4). 824–850. 27 indexed citations
3.
Luzón, M. Victoria, et al.. (2024). An interpretable client decision tree aggregation process for federated learning. Information Sciences. 694. 121711–121711. 4 indexed citations
4.
Rodríguez-Barroso, Nuria, Javier Del Ser, M. Victoria Luzón, & Francisco Herrera. (2024). Defense Strategy against Byzantine Attacks in Federated Machine Learning: Developments towards Explainability. TECNALIA Publications (Fundación TECNALIA Research & Innovation). 1–8. 1 indexed citations
5.
Rodríguez-Barroso, Nuria, Eugenio Martínez‐Cámara, José Camacho-Collados, M. Victoria Luzón, & Francisco Herrera. (2024). Federated Learning for Exploiting Annotators’ Disagreements in Natural Language Processing. Transactions of the Association for Computational Linguistics. 12. 630–648. 3 indexed citations
6.
Herrera, Francisco, et al.. (2024). FLEX: Flexible Federated Learning Framework. Information Fusion. 117. 102792–102792. 4 indexed citations
7.
Rodríguez-Barroso, Nuria, Eugenio Martínez‐Cámara, M. Victoria Luzón, & Francisco Herrera. (2022). Dynamic defense against byzantine poisoning attacks in federated learning. Future Generation Computer Systems. 133. 1–9. 31 indexed citations
8.
López, Miguel Cecilio Botella, Eugenio Martínez‐Cámara, M. Victoria Luzón, & Francisco Herrera. (2021). ADOPS: Aspect Discovery OPinion Summarisation Methodology based on deep learning and subgroup discovery for generating explainable opinion summaries. Knowledge-Based Systems. 231. 107455–107455. 7 indexed citations
9.
Valdivia, Ana, Iti Chaturvedi, M. Victoria Luzón, et al.. (2019). Inconsistencies on TripAdvisor reviews: A unified index between users and Sentiment Analysis Methods. Neurocomputing. 353. 3–16. 55 indexed citations
10.
Valdivia, Ana, M. Victoria Luzón, Erik Cambria, & Francisco Herrera. (2018). Consensus vote models for detecting and filtering neutrality in sentiment analysis. Information Fusion. 44. 126–135. 105 indexed citations
11.
López, Miguel Cecilio Botella, Ana Valdivia, Eugenio Martínez‐Cámara, M. Victoria Luzón, & Francisco Herrera. (2018). E2SAM: Evolutionary ensemble of sentiment analysis methods for domain adaptation. Information Sciences. 480. 273–286. 30 indexed citations
12.
Valdivia, Ana, Eugenio Martínez‐Cámara, Iti Chaturvedi, et al.. (2018). What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. Journal of Ambient Intelligence and Humanized Computing. 11(1). 39–52. 24 indexed citations
13.
Ortín, Francisco, Francisco Javier Melero, & M. Victoria Luzón. (2016). A complete 3D information system for cultural heritage documentation. Journal of Cultural Heritage. 23. 49–57. 69 indexed citations
14.
Torres, Juan Carlos, et al.. (2013). Design of cultural heritage information systems based on information layers. Journal on Computing and Cultural Heritage. 6(4). 1–17. 15 indexed citations
15.
Joan‐Arinyo, Robert, M. Victoria Luzón, & Enrique Yeguas-Bolívar. (2010). Parameter tuning of PBIL and CHC evolutionary algorithms applied to solve the Root Identification Problem. Applied Soft Computing. 11(1). 754–767. 9 indexed citations
16.
Luzón, M. Victoria, et al.. (2010). Scale-dependent and example-based grayscale stippling. Computers & Graphics. 35(1). 160–174. 15 indexed citations
17.
Yeguas-Bolívar, Enrique, Robert Joan‐Arinyo, & M. Victoria Luzón. (2010). Modeling the Performance of Evolutionary Algorithms on the Root Identification Problem: A Case Study with PBIL and CHC Algorithms. Evolutionary Computation. 19(1). 107–135. 7 indexed citations
18.
Pavón, Reyes, Fernando Díaz, Rosalía Laza, & M. Victoria Luzón. (2009). Experimental evaluation of an automatic parameter setting system. Expert Systems with Applications. 37(7). 5224–5238. 2 indexed citations
19.
Joan‐Arinyo, Robert, M. Victoria Luzón, & Enrique Yeguas-Bolívar. (2008). Parameter tunning for PBIL algorithm in geometric constraint solving systems. QRU Quaderns de Recerca en Urbanisme. 37–47. 3 indexed citations
20.
Pavón, Reyes, Fernando Díaz, & M. Victoria Luzón. (2006). An adjustment model in a geometric constraint solving problem. 968–973. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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