Mostefa Golea

838 total citations
20 papers, 502 citations indexed

About

Mostefa Golea is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Mostefa Golea has authored 20 papers receiving a total of 502 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 2 papers in Control and Systems Engineering. Recurrent topics in Mostefa Golea's work include Neural Networks and Applications (18 papers), Machine Learning and Algorithms (12 papers) and Machine Learning and Data Classification (7 papers). Mostefa Golea is often cited by papers focused on Neural Networks and Applications (18 papers), Machine Learning and Algorithms (12 papers) and Machine Learning and Data Classification (7 papers). Mostefa Golea collaborates with scholars based in Canada, Australia and United States. Mostefa Golea's co-authors include Mario Marchand, Joachim Diederich, Alan Tickle, Robert Andrews, P. Ruján, Thomas R. Hancock, Llew Mason, Peter L. Bartlett, Wee Sun Lee and Ross Hayward and has published in prestigious journals such as Neural Computation, Neural Networks and Machine Learning.

In The Last Decade

Mostefa Golea

17 papers receiving 454 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mostefa Golea Canada 8 406 104 88 53 51 20 502
Wang Zheng-ou China 9 233 0.6× 95 0.9× 53 0.6× 101 1.9× 38 0.7× 38 364
Krzysztof Grąbczewski Poland 9 305 0.8× 106 1.0× 55 0.6× 61 1.2× 20 0.4× 26 409
Hakan Altınçay Cyprus 14 348 0.9× 43 0.4× 85 1.0× 110 2.1× 24 0.5× 40 472
Ho-Sung Park South Korea 12 272 0.7× 38 0.4× 45 0.5× 42 0.8× 48 0.9× 38 452
Mark W. Hauschild United States 10 374 0.9× 158 1.5× 35 0.4× 37 0.7× 59 1.2× 15 524
O. Uncu Canada 6 236 0.6× 40 0.4× 37 0.4× 43 0.8× 47 0.9× 12 330
Daniel Graves Canada 8 298 0.7× 47 0.5× 171 1.9× 22 0.4× 57 1.1× 17 428
Shenkai Gu United Kingdom 6 295 0.7× 79 0.8× 84 1.0× 31 0.6× 31 0.6× 8 376
Ciro Castiello Italy 11 251 0.6× 60 0.6× 87 1.0× 40 0.8× 24 0.5× 44 375
Christian Döring Germany 7 203 0.5× 49 0.5× 149 1.7× 35 0.7× 23 0.5× 10 360

Countries citing papers authored by Mostefa Golea

Since Specialization
Citations

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

Fields of papers citing papers by Mostefa Golea

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mostefa Golea

This figure shows the co-authorship network connecting the top 25 collaborators of Mostefa Golea. A scholar is included among the top collaborators of Mostefa Golea 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 Mostefa Golea. Mostefa Golea 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.
Mason, Llew, Peter L. Bartlett, & Mostefa Golea. (2002). Generalization Error of Combined Classifiers. Journal of Computer and System Sciences. 65(2). 415–438. 6 indexed citations
2.
Tickle, Alan, Mostefa Golea, Ross Hayward, & Joachim Diederich. (2002). The truth is in there: current issues in extracting rules from trained feedforward artificial neural networks. Proceedings of International Conference on Neural Networks (ICNN'97). 4. 2530–2534. 3 indexed citations
3.
Sakakibara, Yasubumi & Mostefa Golea. (2002). Simple recurrent networks as generalized hidden Markov models with distributed representations. 2. 979–984. 1 indexed citations
4.
Tickle, Alan, Robert Andrews, Mostefa Golea, & Joachim Diederich. (1998). The truth will come to light: directions and challenges in extracting the knowledge embedded within trained artificial neural networks. IEEE Transactions on Neural Networks. 9(6). 1057–1068. 262 indexed citations
5.
Golea, Mostefa, Peter L. Bartlett, Wee Sun Lee, & Llew Mason. (1997). Generalization in Decision Trees and DNF: Does Size Matter?. Neural Information Processing Systems. 10. 259–265. 16 indexed citations
6.
Golea, Mostefa, Mario Marchand, & Thomas R. Hancock. (1996). On learning μ-perceptron networks on the uniform distribution. Neural Networks. 9(1). 67–82. 4 indexed citations
7.
Golea, Mostefa, et al.. (1996). Columnar recurrent neural network and time series analysis. 32(2). 183–191. 1 indexed citations
8.
Golea, Mostefa & Mario Marchand. (1994). On learning simple deterministic and probabilistic neural concepts. 47–60.
9.
Hancock, Thomas R., Mostefa Golea, & Mario Marchand. (1994). Learning Nonoverlapping Perceptron Networks from Examples and Membership Queries. Machine Learning. 16(3). 161–183. 8 indexed citations
10.
Golea, Mostefa. (1994). AVERAGE CASE ANALYSIS OF AN HEBB-TYPE RULE THAT FINDS THE NETWORK CONNECTIVITY. International Journal of Neural Systems. 5(2). 115–122.
11.
Hancock, Thomas R., Mostefa Golea, & Mario Marchand. (1994). Learning nonoverlapping perceptron networks from examples and membership queries. Machine Learning. 16(3). 161–183. 5 indexed citations
12.
Golea, Mostefa & Mario Marchand. (1993). Learning curves of the clipped Hebb rule for networks with binary weights. Journal of Physics A Mathematical and General. 26(21). 5751–5766. 4 indexed citations
13.
Marchand, Mario & Mostefa Golea. (1993). On learning simple neural concepts: from halfspace intersections to neural decision lists. Network Computation in Neural Systems. 4(1). 67–85. 29 indexed citations
14.
Marchand, Mario & Mostefa Golea. (1993). An Approximation Algorithm to Find the Largest Linearly Separable Subset of Training Examples. 1 indexed citations
15.
Marchand, Mario & Mostefa Golea. (1993). On learning simple neural concepts: from halfspace intersections to neural decision lists. Network Computation in Neural Systems. 4(1). 67–85. 14 indexed citations
16.
Golea, Mostefa & Mario Marchand. (1993). On Learning Perceptrons with Binary Weights. Neural Computation. 5(5). 767–782. 9 indexed citations
17.
Golea, Mostefa & Mario Marchand. (1993). Average case analysis of the clipped Hebb rule for nonoverlapping perception networks. 151–157. 3 indexed citations
18.
Golea, Mostefa, Mario Marchand, & Thomas R. Hancock. (1992). On Learning µ-Perceptron Networks with Binary Weights. Neural Information Processing Systems. 591–598. 7 indexed citations
19.
Marchand, Mario, Mostefa Golea, & P. Ruján. (1990). A Convergence Theorem for Sequential Learning in Two-Layer Perceptrons. Europhysics Letters (EPL). 11(6). 487–492. 87 indexed citations
20.
Golea, Mostefa & Mario Marchand. (1990). A Growth Algorithm for Neural Network Decision Trees. Europhysics Letters (EPL). 12(3). 205–210. 42 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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