This map shows the geographic impact of Nir Ailon'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 Nir Ailon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nir Ailon more than expected).
This network shows the impact of papers produced by Nir Ailon. 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 Nir Ailon. The network helps show where Nir Ailon may publish in the future.
Co-authorship network of co-authors of Nir Ailon
This figure shows the co-authorship network connecting the top 25 collaborators of Nir Ailon.
A scholar is included among the top collaborators of Nir Ailon 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 Nir Ailon. Nir Ailon 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.
Ailon, Nir, et al.. (2018). A New and Flexible Approach to the Analysis of Paired Comparison Data. Journal of Machine Learning Research. 19(60). 1–29.5 indexed citations
2.
Hoffer, Elad & Nir Ailon. (2017). Semi-supervised deep learning by metric embedding. arXiv (Cornell University).3 indexed citations
Ailon, Nir, Yudong Chen, & Huan Xu. (2015). Iterative and active graph clustering using trace norm minimization without cluster size constraints. Journal of Machine Learning Research. 16(1). 455–490.4 indexed citations
7.
Ailon, Nir. (2014). Improved Bounds for Online Learning Over the Permutahedron and Other Ranking Polytopes. International Conference on Artificial Intelligence and Statistics. 29–37.9 indexed citations
Ailon, Nir, et al.. (2011). A New Active Learning Scheme with Applications to Learning to Rank from Pairwise Preferences. arXiv (Cornell University).4 indexed citations
10.
Ailon, Nir. (2011). Active Learning Ranking from Pairwise Preferences with Almost Optimal Query Complexity. Neural Information Processing Systems. 24. 810–818.27 indexed citations
Ailon, Nir. (2008). Reconciling Real Scores with Binary Comparisons: A New Logistic Based Model for Ranking. Neural Information Processing Systems. 21. 25–32.2 indexed citations
15.
Ailon, Nir. (2008). Reconciling real scores with binary comparisons: a unified logistic model for ranking. Neural Information Processing Systems. 25–32.2 indexed citations
16.
Ailon, Nir, Moses Charikar, & Alantha Newman. (2008). Aggregating inconsistent information. Journal of the ACM. 55(5). 1–27.311 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.