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.
Countries citing papers authored by Roberto J. Bayardo
Since
Specialization
Citations
This map shows the geographic impact of Roberto J. Bayardo'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 Roberto J. Bayardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto J. Bayardo more than expected).
Fields of papers citing papers by Roberto J. Bayardo
This network shows the impact of papers produced by Roberto J. Bayardo. 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 Roberto J. Bayardo. The network helps show where Roberto J. Bayardo may publish in the future.
Co-authorship network of co-authors of Roberto J. Bayardo
This figure shows the co-authorship network connecting the top 25 collaborators of Roberto J. Bayardo.
A scholar is included among the top collaborators of Roberto J. Bayardo 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 Roberto J. Bayardo. Roberto J. Bayardo 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.
Hummel, Patrick, et al.. (2017). Allocation of Advertisement Extensions & Formats.1 indexed citations
Bayardo, Roberto J., et al.. (2000). Counting Models Using Connected Components. National Conference on Artificial Intelligence. 157–162.99 indexed citations
11.
Ramakrishnan, Raghu, et al.. (2000). Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining. Knowledge Discovery and Data Mining.8 indexed citations
Bayardo, Roberto J.. (1998). Efficiently mining long patterns from databases. 85–93.825 indexed citations breakdown →
17.
Bayardo, Roberto J. & Robert Schrag. (1997). Using CSP look-back techniques to solve real-world SAT instances. National Conference on Artificial Intelligence. 203–208.320 indexed citations
18.
Bayardo, Roberto J. & Daniel P. Miranker. (1996). A complexity analysis of space-bounded learning algorithms for the constraint satisfaction problem. National Conference on Artificial Intelligence. 298–304.52 indexed citations
Bayardo, Roberto J. & Daniel P. Miranker. (1995). On the space-time trade-off in solving constraint satisfaction problems. International Joint Conference on Artificial Intelligence. 558–562.27 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.