Carlos Domingo

1.2k total citations
12 papers, 250 citations indexed

About

Carlos Domingo is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Carlos Domingo has authored 12 papers receiving a total of 250 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 2 papers in Computer Networks and Communications and 2 papers in Information Systems. Recurrent topics in Carlos Domingo's work include Machine Learning and Algorithms (5 papers), Machine Learning and Data Classification (3 papers) and Algorithms and Data Compression (3 papers). Carlos Domingo is often cited by papers focused on Machine Learning and Algorithms (5 papers), Machine Learning and Data Classification (3 papers) and Algorithms and Data Compression (3 papers). Carlos Domingo collaborates with scholars based in Japan, Spain and United States. Carlos Domingo's co-authors include Osamu Watanabe, Ricard Gavaldà, Leonard Pitt, Nina Mishra, Toniann Pitassi, Marı́a Luisa Bonet, Jaime Ricardo Valenzuela González, A. de Diego Damiá, Tomasz Adamek and James Abello and has published in prestigious journals such as Machine Learning, Data Mining and Knowledge Discovery and Information Processing Letters.

In The Last Decade

Carlos Domingo

10 papers receiving 231 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Carlos Domingo Japan	6	189	69	58	32	16	12	250
Josip Djolonga Switzerland	7	123 0.7×	37 0.5×	48 0.8×	11 0.3×	8 0.5×	12	165
Madhav Jha United States	9	150 0.8×	100 1.4×	74 1.3×	18 0.6×	66 4.1×	17	294
Kush Bhatia United States	6	279 1.5×	33 0.5×	78 1.3×	44 1.4×	15 0.9×	12	341
Yingke Chen China	9	121 0.6×	53 0.8×	66 1.1×	18 0.6×	18 1.1×	27	221
Bakh Khoussainov New Zealand	10	87 0.5×	96 1.4×	37 0.6×	64 2.0×	36 2.3×	31	227
Karl Pfleger United States	5	117 0.6×	27 0.4×	23 0.4×	58 1.8×	21 1.3×	7	166
Francisco Fernández de Vega Spain	10	159 0.8×	30 0.4×	40 0.7×	23 0.7×	47 2.9×	45	266
Henrik Großkreutz Germany	9	182 1.0×	47 0.7×	49 0.8×	77 2.4×	30 1.9×	21	253
Christiane Lammersen Germany	4	150 0.8×	18 0.3×	34 0.6×	28 0.9×	41 2.6×	7	208
Weiqi Li China	9	100 0.5×	22 0.3×	86 1.5×	36 1.1×	59 3.7×	24	204

Countries citing papers authored by Carlos Domingo

Since Specialization

Citations

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

Fields of papers citing papers by Carlos Domingo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Carlos Domingo

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Domingo, Carlos, et al.. (2022). Clinical Features and Outcomes Associated with Bronchial Asthma Among COVID-19 Hospitalized Patients. Journal of Asthma and Allergy. Volume 15. 775–781. 3 indexed citations

2.

Adamek, Tomasz, et al.. (2010). Reconocimiento visual móvil: el futuro de la realidad aumentada móvil. Dialnet (Universidad de la Rioja). 74(84). 10–12.

3.

Domingo, Carlos, et al.. (2008). La Web 2.0. Una revolución social y creativa. Dialnet (Universidad de la Rioja). 134–141. 3 indexed citations

4.

García‐Fernández, Pablo, et al.. (2006). Modelos educactivos: del Taylorismo al e-learning. 4(4). 13.

5.

Bonet, Marı́a Luisa, et al.. (2004). Non-Automatizability of Bounded-Depth Frege Proofs. Computational Complexity. 13(1-2). 47–68. 22 indexed citations

6.

Bonet, Marı́a Luisa, et al.. (2003). Non-automatizability of bounded-depth Frege proofs. 39. 15–23. 6 indexed citations

7.

Domingo, Carlos, Ricard Gavaldà, & Osamu Watanabe. (2002). Adaptive Sampling Methods for Scaling Up Knowledge Discovery Algorithms. Data Mining and Knowledge Discovery. 6(2). 131–152. 65 indexed citations

8.

Domingo, Carlos & Osamu Watanabe. (2000). MadaBoost: A Modification of AdaBoost. Tokyo Tech Research Repository (Tokyo Institute of Technology). 180–189. 109 indexed citations

9.

Domingo, Carlos, Nina Mishra, & Leonard Pitt. (1999). Efficient Read-Restricted Monotone CNF/DNF Dualization by Learning with Membership Queries. Machine Learning. 37(1). 89–110. 34 indexed citations

10.

Domingo, Carlos, et al.. (1997). Partial Occam's Razor and its applications. Information Processing Letters. 64(4). 179–185. 5 indexed citations

11.

Domingo, Carlos, John Shawe‐Taylor, Hans L. Bodlaender, & James Abello. (1994). Learning minor closed graph classes with membership and equivalence queries. ePrints Soton (University of Southampton). 1 indexed citations

12.

Domingo, Carlos, et al.. (1994). Old and new models of Venezuela. RePEc: Research Papers in Economics. 19(9). 27–53. 2 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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