André M. S. Barreto

526 total citations
18 papers, 316 citations indexed

About

André M. S. Barreto is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, André M. S. Barreto has authored 18 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 8 papers in Computational Theory and Mathematics and 3 papers in Control and Systems Engineering. Recurrent topics in André M. S. Barreto's work include Reinforcement Learning in Robotics (7 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Evolutionary Algorithms and Applications (4 papers). André M. S. Barreto is often cited by papers focused on Reinforcement Learning in Robotics (7 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Evolutionary Algorithms and Applications (4 papers). André M. S. Barreto collaborates with scholars based in Brazil, Canada and France. André M. S. Barreto's co-authors include Hélio J. C. Barbosa, Laurent E. Dardenne, Mélaine A. Kuenemann, Isabella Alvim Guedes, Eduardo Krempser, Olivier Spérandio, Maria A. Miteva, Heder S. Bernardino, Artur Ziviani and Matheus R. F. Mendonça and has published in prestigious journals such as IEEE Transactions on Automatic Control, Scientific Reports and ACM Computing Surveys.

In The Last Decade

André M. S. Barreto

18 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
André M. S. Barreto Brazil	9	131	115	84	26	24	18	316
Jian Jiang China	11	93 0.7×	45 0.4×	68 0.8×	26 1.0×	6 0.3×	35	280
Yasuhiro Fujita Japan	12	60 0.5×	47 0.4×	166 2.0×	49 1.9×	76 3.2×	61	714
Rui Meng China	11	42 0.3×	77 0.7×	73 0.9×	13 0.5×	39 1.6×	51	412
Hang Xu China	9	245 1.9×	283 2.5×	82 1.0×	3 0.1×	27 1.1×	27	517
Young-Seob Jeong South Korea	14	61 0.5×	230 2.0×	57 0.7×	12 0.5×	4 0.2×	63	571
Shin Ando Japan	11	38 0.3×	224 1.9×	150 1.8×	13 0.5×	16 0.7×	42	391

Countries citing papers authored by André M. S. Barreto

Since Specialization

Citations

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

Fields of papers citing papers by André M. S. Barreto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by André M. S. Barreto. 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 André M. S. Barreto. The network helps show where André M. S. Barreto may publish in the future.

Co-authorship network of co-authors of André M. S. Barreto

This figure shows the co-authorship network connecting the top 25 collaborators of André M. S. Barreto. A scholar is included among the top collaborators of André M. S. Barreto 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 André M. S. Barreto. André M. S. Barreto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Mendonça, Matheus R. F., André M. S. Barreto, & Artur Ziviani. (2022). Efficient information diffusion in time-varying graphs through deep reinforcement learning. World Wide Web. 25(6). 2535–2560. 4 indexed citations

Guedes, Isabella Alvim, André M. S. Barreto, Eduardo Krempser, et al.. (2021). New machine learning and physics-based scoring functions for drug discovery. Scientific Reports. 11(1). 3198–3198. 133 indexed citations

Mendonça, Matheus R. F., André M. S. Barreto, & Artur Ziviani. (2020). Approximating Network Centrality Measures Using Node Embedding and Machine Learning. IEEE Transactions on Network Science and Engineering. 8(1). 220–230. 19 indexed citations

Mendonça, Matheus R. F., Artur Ziviani, & André M. S. Barreto. (2019). Graph-Based Skill Acquisition For Reinforcement Learning. ACM Computing Surveys. 52(1). 1–26. 10 indexed citations

Todorov, Marcos G., et al.. (2018). Online TD(A) for discrete-time Markov jump linear systems. 2229–2234. 5 indexed citations

Todorov, Marcos G., et al.. (2017). Count-based quadratic control of Markov jump linear systems with unknown transition probabilities. 6. 4315–4320. 2 indexed citations

Barreto, André M. S., et al.. (2016). Practical kernel-based reinforcement learning. Europe PMC (PubMed Central). 17(1). 2372–2441. 15 indexed citations

Barreto, André M. S., et al.. (2015). An expectation-maximization algorithm to compute a stochastic factorization from data. International Conference on Artificial Intelligence. 3329–3336. 1 indexed citations

Farahmand, Amir‐massoud, Doina Precup, André M. S. Barreto, & Mohammad Ghavamzadeh. (2015). Classification-Based Approximate Policy Iteration. IEEE Transactions on Automatic Control. 60(11). 2989–2993. 3 indexed citations

10.

Barreto, André M. S., Joëlle Pineau, & Doina Precup. (2014). Policy Iteration Based on Stochastic Factorization. Journal of Artificial Intelligence Research. 50. 763–803. 8 indexed citations

11.

Barreto, André M. S. & Marcelo D. Fragoso. (2011). Computing the Stationary Distribution of a Finite Markov Chain Through Stochastic Factorization. SIAM Journal on Matrix Analysis and Applications. 32(4). 1513–1523. 8 indexed citations

12.

Barreto, André M. S. & Marcelo D. Fragoso. (2011). Lumping the States of a Finite Markov Chain Through Stochastic Factorization. IFAC Proceedings Volumes. 44(1). 4206–4211. 4 indexed citations

13.

Barreto, André M. S., Heder S. Bernardino, & Hélio J. C. Barbosa. (2010). Probabilistic performance profiles for the experimental evaluation of stochastic algorithms. 751–758. 4 indexed citations

14.

Barbosa, Hélio J. C., Heder S. Bernardino, & André M. S. Barreto. (2010). Using performance profiles to analyze the results of the 2006 CEC constrained optimization competition. 1–8. 42 indexed citations

15.

Barreto, André M. S., Douglas A. Augusto, & Hélio J. C. Barbosa. (2009). On the characteristics of sequential decision problems and their impact on evolutionary computation. 1767–1768. 1 indexed citations

16.

Barreto, André M. S., Hélio J. C. Barbosa, & Nelson F. F. Ebecken. (2006). GOLS—Genetic orthogonal least squares algorithm for training RBF networks. Neurocomputing. 69(16-18). 2041–2064. 20 indexed citations

17.

Barreto, André M. S. & Hélio J. C. Barbosa. (2002). Graph layout using a genetic algorithm. 179–184. 12 indexed citations

18.

Barbosa, Hélio J. C. & André M. S. Barreto. (2001). An interactive genetic algorithm with co-evolution of weights for multiobjective problems. Genetic and Evolutionary Computation Conference. 8(6). 203–210. 25 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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