Alberto Suárez

2.8k total citations
67 papers, 1.9k citations indexed

About

Alberto Suárez is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Statistics and Probability. According to data from OpenAlex, Alberto Suárez has authored 67 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 12 papers in Statistical and Nonlinear Physics and 12 papers in Statistics and Probability. Recurrent topics in Alberto Suárez's work include Machine Learning and Data Classification (14 papers), Neural Networks and Applications (12 papers) and Face and Expression Recognition (10 papers). Alberto Suárez is often cited by papers focused on Machine Learning and Data Classification (14 papers), Neural Networks and Applications (12 papers) and Face and Expression Recognition (10 papers). Alberto Suárez collaborates with scholars based in Spain, United States and Belgium. Alberto Suárez's co-authors include Gonzalo Martínez-Muñoz, Daniel Hernández-Lobato, R. Silbey, Rubén Ruiz-Torrubiano, Irwin Oppenheim, James F. Lutsko, José Miguel Hernández-Lobato, Nader Fathianpour, John Ross and David R. Reichman and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Alberto Suárez

64 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alberto Suárez Spain 23 1.0k 358 311 261 178 67 1.9k
Peter Harremoës Denmark 15 688 0.7× 141 0.4× 157 0.5× 107 0.4× 448 2.5× 61 1.7k
Dominik Janzing Germany 27 2.1k 2.0× 510 1.4× 124 0.4× 247 0.9× 303 1.7× 94 2.8k
Bruce Jay Collings United States 13 409 0.4× 90 0.3× 432 1.4× 284 1.1× 153 0.9× 21 2.6k
John E. Shore United States 19 921 0.9× 136 0.4× 408 1.3× 214 0.8× 763 4.3× 51 2.4k
Sandro Ridella Italy 24 1.3k 1.2× 145 0.4× 613 2.0× 92 0.4× 124 0.7× 136 3.1k
Stefan Zohren United Kingdom 14 525 0.5× 126 0.4× 75 0.2× 583 2.2× 183 1.0× 77 1.7k
Flemming Topsøe Denmark 16 498 0.5× 62 0.2× 150 0.5× 134 0.5× 354 2.0× 53 1.4k
Alexandre d’Aspremont France 20 768 0.7× 79 0.2× 535 1.7× 213 0.8× 86 0.5× 60 2.9k
Peter Grünwald Netherlands 21 923 0.9× 48 0.1× 95 0.3× 262 1.0× 143 0.8× 98 1.8k
Amlan Chakrabarti India 24 916 0.9× 210 0.6× 383 1.2× 92 0.4× 296 1.7× 317 2.8k

Countries citing papers authored by Alberto Suárez

Since Specialization
Citations

This map shows the geographic impact of Alberto Suárez'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 Alberto Suárez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alberto Suárez more than expected).

Fields of papers citing papers by Alberto Suárez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alberto Suárez. 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 Alberto Suárez. The network helps show where Alberto Suárez may publish in the future.

Co-authorship network of co-authors of Alberto Suárez

This figure shows the co-authorship network connecting the top 25 collaborators of Alberto Suárez. A scholar is included among the top collaborators of Alberto Suárez 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 Alberto Suárez. Alberto Suárez 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.
Suárez, Alberto, et al.. (2024). scikit-fda: A Python Package for Functional Data Analysis. Journal of Statistical Software. 109(2). 14 indexed citations
2.
Suárez, Alberto, et al.. (2022). Classification of Functional Data: A Comparative Study. Biblos-e Archivo (Universidad Autónoma de Madrid). 866–871. 2 indexed citations
3.
Martínez-Muñoz, Gonzalo, et al.. (2021). Building heterogeneous ensembles by pooling homogeneous ensembles. International Journal of Machine Learning and Cybernetics. 13(2). 551–558. 22 indexed citations
4.
Soto, Víctor, Alberto Suárez, & Gonzalo Martínez-Muñoz. (2016). An urn model for majority voting in classification ensembles. Biblos-e Archivo (Universidad Autónoma de Madrid). 29. 4437–4445. 3 indexed citations
5.
Martínez-Muñoz, Gonzalo, et al.. (2015). Small margin ensembles can be robust to class-label noise. Neurocomputing. 160. 18–33. 9 indexed citations
6.
Martínez-Muñoz, Gonzalo, et al.. (2014). Improving the robustness of bagging with reduced sampling size. Biblos-e Archivo (Universidad Autónoma de Madrid). 5 indexed citations
7.
Hernández-Lobato, José Miguel, Daniel Hernández-Lobato, & Alberto Suárez. (2014). Expectation propagation in linear regression models with spike-and-slab priors. Machine Learning. 99(3). 437–487. 40 indexed citations
8.
Suárez, Alberto, et al.. (2013). Critical sample size for the L p -norm estimator in linear regression models. Winter Simulation Conference. 1047–1056.
9.
Hernández-Lobato, Daniel, et al.. (2013). Statistical tests for the detection of the arrow of time in vector autoregressive models. International Joint Conference on Artificial Intelligence. 1544–1550. 1 indexed citations
10.
Hernández-Lobato, Daniel, Gonzalo Martínez-Muñoz, & Alberto Suárez. (2012). On the independence of the individual predictions in parallel randomized ensembles. Biblos-e Archivo (Universidad Autónoma de Madrid). 3 indexed citations
11.
Hernández-Lobato, Daniel, Gonzalo Martínez-Muñoz, & Alberto Suárez. (2012). How large should ensembles of classifiers be?. Pattern Recognition. 46(5). 1323–1336. 39 indexed citations
12.
Suárez, Alberto, et al.. (2011). Producción y calidad de varias gramíneas en cultivo monofito y en asociación. POLI-RED (Revistas Digitales Politécnicas) (La Universidad Politécnica de Madrid). 2021(20). 3–17. 3 indexed citations
13.
Hernández-Lobato, José Miguel, et al.. (2011). Gaussianity measures for detecting the direction of causal time series. International Joint Conference on Artificial Intelligence. 1318–1323. 4 indexed citations
14.
Ruiz-Torrubiano, Rubén & Alberto Suárez. (2010). Hybrid Approaches and Dimensionality Reduction for Portfolio Selection with Cardinality Constraints. IEEE Computational Intelligence Magazine. 5(2). 92–107. 70 indexed citations
15.
Martínez-Muñoz, Gonzalo & Alberto Suárez. (2006). Using boosting to prune bagging ensembles. Pattern Recognition Letters. 28(1). 156–165. 85 indexed citations
16.
Martínez-Muñoz, Gonzalo & Alberto Suárez. (2005). Switching class labels to generate classification ensembles. Pattern Recognition. 38(10). 1483–1494. 58 indexed citations
17.
Martínez-Muñoz, Gonzalo & Alberto Suárez. (2004). Using All Data to Generate Decision Tree Ensembles. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews). 34(4). 393–397. 16 indexed citations
18.
Suárez, Alberto & James F. Lutsko. (1999). Globally optimal fuzzy decision trees for classification and regression. IEEE Transactions on Pattern Analysis and Machine Intelligence. 21(12). 1297–1311. 119 indexed citations
19.
Suárez, Alberto & Jean Pierre Boon. (1997). Nonlinear lattice gas hydrodynamics. Journal of Statistical Physics. 87(5-6). 1123–1130. 1 indexed citations
20.
Hunt, Katharine L. C., et al.. (1995). Thermodynamic and stochastic theory of nonequilibrium systems: Fluctuation probabilities and excess work. The Journal of Chemical Physics. 102(11). 4548–4562. 22 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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