Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Countries citing papers authored by Pedro Domingos
Since
Specialization
Citations
This map shows the geographic impact of Pedro Domingos'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 Pedro Domingos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro Domingos more than expected).
This network shows the impact of papers produced by Pedro Domingos. 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 Pedro Domingos. The network helps show where Pedro Domingos may publish in the future.
Co-authorship network of co-authors of Pedro Domingos
This figure shows the co-authorship network connecting the top 25 collaborators of Pedro Domingos.
A scholar is included among the top collaborators of Pedro Domingos 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 Pedro Domingos. Pedro Domingos is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Gens, Robert & Pedro Domingos. (2014). Deep Symmetry Networks. Neural Information Processing Systems. 27. 2537–2545.76 indexed citations
4.
Kok, Stanley & Pedro Domingos. (2010). Using structural motifs for learning Markov logic networks. National University of Singapore. 46–51.1 indexed citations
5.
Kok, Stanley & Pedro Domingos. (2010). Learning Markov Logic Networks Using Structural Motifs. International Conference on Machine Learning. 551–558.58 indexed citations
6.
Gogate, Vibhav & Pedro Domingos. (2010). Exploiting logical structure in lifted probabilistic inference. National Conference on Artificial Intelligence. 19–25.11 indexed citations
7.
Kiddon, Chloé & Pedro Domingos. (2010). Leveraging ontologies for lifted probabilistic inference and learning. National Conference on Artificial Intelligence. 40–45.2 indexed citations
8.
Lowd, Daniel & Pedro Domingos. (2010). Approximate Inference by Compilation to Arithmetic Circuits. Neural Information Processing Systems. 23. 1477–1485.5 indexed citations
9.
Poon, Hoifung & Pedro Domingos. (2010). Machine reading: a Killer app for statistical relational AI. National Conference on Artificial Intelligence. 76–81.12 indexed citations
10.
Poon, Hoifung, et al.. (2008). A general method for reducing the complexity of relational inference and its application to MCMC. National Conference on Artificial Intelligence. 1075–1080.48 indexed citations
11.
Lowd, Daniel & Pedro Domingos. (2007). Recursive random fields. International Joint Conference on Artificial Intelligence. 950–955.10 indexed citations
12.
Poon, Hoifung & Pedro Domingos. (2006). Sound and efficient inference with probabilistic and deterministic dependencies. National Conference on Artificial Intelligence. 458–463.155 indexed citations
13.
Singla, Parag & Pedro Domingos. (2005). Collective object identification. International Joint Conference on Artificial Intelligence. 1636–1637.3 indexed citations
14.
Dhamankar, Robin, et al.. (2004). iMAP: Discovering Complex Mappings between Database Schemas.. International Conference on Management of Data. 383–394.46 indexed citations
15.
Getoor, Lise, Ted E. Senator, Pedro Domingos, & Christos Faloutsos. (2003). Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. Knowledge Discovery and Data Mining.341 indexed citations
16.
Sanghai, Sumit, Pedro Domingos, & Daniel S. Weld. (2003). Dynamic probabilistic relational models. International Joint Conference on Artificial Intelligence. 992–997.46 indexed citations
17.
Anderson, Corin R., Pedro Domingos, & Daniel S. Weld. (2001). Adaptive web navigation for wireless devices. International Joint Conference on Artificial Intelligence. 879–884.66 indexed citations
18.
Lau, Tessa, Pedro Domingos, & Daniel S. Weld. (2000). Version Space Algebra and its Application to Programming by Demonstration. International Conference on Machine Learning. 527–534.63 indexed citations
Domingos, Pedro. (1995). The RISE 2.0 System: A Case Study in Multistrategy Learning. eScholarship (California Digital Library).7 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.