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.
Machine learning and the physical sciences
20191.4k citationsGiuseppe Carleo, J. I. Cirac et al.Reviews of Modern Physicsprofile →
Selective Sampling Using the Query by Committee Algorithm
Countries citing papers authored by Naftali Tishby
Since
Specialization
Citations
This map shows the geographic impact of Naftali Tishby'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 Naftali Tishby with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naftali Tishby more than expected).
This network shows the impact of papers produced by Naftali Tishby. 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 Naftali Tishby. The network helps show where Naftali Tishby may publish in the future.
Co-authorship network of co-authors of Naftali Tishby
This figure shows the co-authorship network connecting the top 25 collaborators of Naftali Tishby.
A scholar is included among the top collaborators of Naftali Tishby 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 Naftali Tishby. Naftali Tishby is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zaslavsky, Noga, et al.. (2019). Evolution and efficiency in color naming: The case of Nafaanra.. Cognitive Science. 68.1 indexed citations
3.
Carleo, Giuseppe, J. I. Cirac, K. Cranmer, et al.. (2019). Machine learning and the physical sciences. Reviews of Modern Physics. 91(4).1446 indexed citations breakdown →
Seldin, Yevgeny & Naftali Tishby. (2010). PAC-Bayesian Analysis of Co-clustering and Beyond. Journal of Machine Learning Research. 11(117). 3595–3646.36 indexed citations
6.
Sabato, Sivan, Nathan Srebro, & Naftali Tishby. (2010). Reducing Label Complexity by Learning From Bags. International Conference on Artificial Intelligence and Statistics. 685–692.6 indexed citations
7.
Krupka, Eyal, Amir Navot, & Naftali Tishby. (2008). Learning to Select Features using their Properties. Journal of Machine Learning Research. 9(77). 2349–2376.13 indexed citations
8.
Globerson, Amir, Gal Chechik, Fernando D. Pereira, & Naftali Tishby. (2006). Embedding heterogeneous data using statistical models. Suppl 28. 1605–1608.3 indexed citations
9.
Gilad-Bachrach, Ran, Amir Navot, & Naftali Tishby. (2005). Query by Committee Made Real. Neural Information Processing Systems. 18. 443–450.52 indexed citations
10.
Krupka, Eyal & Naftali Tishby. (2005). Generalization in Clustering with Unobserved Features. Neural Information Processing Systems. 18. 683–690.7 indexed citations
11.
Navot, Amir, Lavi Shpigelman, Naftali Tishby, & Eilon Vaadia. (2005). Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity. Neural Information Processing Systems. 18. 996–1002.69 indexed citations
Globerson, Amir & Naftali Tishby. (2003). Sufficient dimensionality reduction. Journal of Machine Learning Research. 3. 1307–1331.50 indexed citations
14.
Bekkerman, Ron, Ran El‐Yaniv, Naftali Tishby, & Yoad Winter. (2003). Distributional word clusters vs. words for text categorization. Journal of Machine Learning Research. 3. 1183–1208.186 indexed citations
15.
Chechik, Gal, Amir Globerson, Naftali Tishby, & Yair Weiss. (2003). Information Bottleneck for Gaussian Variables. Journal of Machine Learning Research. 16(6). 1213–1220.19 indexed citations
16.
Globerson, Amir, Gal Chechik, & Naftali Tishby. (2002). Sufficient dimensionality reduction with irrelevance statistics. arXiv (Cornell University). 281–288.2 indexed citations
17.
Bejerano, Gill, et al.. (2001). Extraction of Protein Domains and Signatures through Unsupervised Statistical Sequence Segmentation.
Fine, Shai, et al.. (1999). Noise Tolerant Learning Using Early Predictors.
20.
Seung, H. Sebastian, Haim Sompolinsky, & Naftali Tishby. (1991). Learning curves in large neural networks. Conference on Learning Theory. 112–127.9 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.