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.
Finite-time Analysis of the Multiarmed Bandit Problem
20023.1k citationsNicolò Cesa‐Bianchi, Paul Fischer et al.profile →
Prediction, Learning, and Games
20061.6k citationsNicolò Cesa‐Bianchi, Gábor Lugosiprofile →
The Nonstochastic Multiarmed Bandit Problem
20021.1k citationsNicolò Cesa‐Bianchi et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Nicolò Cesa‐Bianchi
Since
Specialization
Citations
This map shows the geographic impact of Nicolò Cesa‐Bianchi'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 Nicolò Cesa‐Bianchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolò Cesa‐Bianchi more than expected).
Fields of papers citing papers by Nicolò Cesa‐Bianchi
This network shows the impact of papers produced by Nicolò Cesa‐Bianchi. 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 Nicolò Cesa‐Bianchi. The network helps show where Nicolò Cesa‐Bianchi may publish in the future.
Co-authorship network of co-authors of Nicolò Cesa‐Bianchi
This figure shows the co-authorship network connecting the top 25 collaborators of Nicolò Cesa‐Bianchi.
A scholar is included among the top collaborators of Nicolò Cesa‐Bianchi 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 Nicolò Cesa‐Bianchi. Nicolò Cesa‐Bianchi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Frasca, Marco & Nicolò Cesa‐Bianchi. (2018). Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction.. arXiv (Cornell University).1 indexed citations
3.
Cesa‐Bianchi, Nicolò & Ohad Shamir. (2018). Bandit Regret Scaling with the Effective Loss Range. 83. 128–151.1 indexed citations
4.
Cesa‐Bianchi, Nicolò, Claudio Gentile, & Giovanni Zappella. (2013). A Gang of Bandits. arXiv (Cornell University). 26. 737–745.17 indexed citations
5.
Cesa‐Bianchi, Nicolò, et al.. (2013). Regret Minimization for Branching Experts. IrInSubria (University of Insubria). 30. 618–638.2 indexed citations
6.
Cesa‐Bianchi, Nicolò, et al.. (2013). Random spanning trees and the prediction ofweighted graphs. Journal of Machine Learning Research. 14(1). 1251–1284.2 indexed citations
7.
Cesa‐Bianchi, Nicolò, et al.. (2012). A Linear Time Active Learning Algorithm for Link Classification. arXiv (Cornell University). 25. 1610–1618.2 indexed citations
8.
Cesa‐Bianchi, Nicolò, Gábor Lugosi, Pierre Gaillard, & Gilles Stoltz. (2012). Mirror descent meets fixed share (and feels no regret. HAL (Le Centre pour la Communication Scientifique Directe).5 indexed citations
9.
Cesa‐Bianchi, Nicolò, Pierre Gaillard, Gábor Lugosi, & Gilles Stoltz. (2012). A New Look at Shifting Regret. arXiv (Cornell University).6 indexed citations
10.
Cesa‐Bianchi, Nicolò, et al.. (2011). See the Tree Through the Lines: The Shazoo Algorithm. arXiv (Cornell University). 24. 1584–1592.14 indexed citations
Cesa‐Bianchi, Nicolò, et al.. (2008). Linear Algorithms for Online Multitask Classification. Journal of Machine Learning Research. 11(97). 251–262.11 indexed citations
13.
Cesa‐Bianchi, Nicolò, et al.. (2008). Linear Classification and Selective Sampling Under Low Noise Conditions. Neural Information Processing Systems. 21. 249–256.16 indexed citations
14.
Cesa‐Bianchi, Nicolò, et al.. (2006). Worst-Case Analysis of Selective Sampling for Linear Classification. Journal of Machine Learning Research. 7(44). 1205–1230.65 indexed citations
15.
Cesa‐Bianchi, Nicolò, et al.. (2004). Incremental Algorithms for Hierarchical Classification. Journal of Machine Learning Research. 17(2). 233–240.90 indexed citations
16.
Cesa‐Bianchi, Nicolò, et al.. (2004). Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms. Neural Information Processing Systems. 17. 241–248.17 indexed citations
17.
Shawe‐Taylor, John, Nicola Cancedda, Nicolò Cesa‐Bianchi, et al.. (2002). Kernel Methods for Document Filtering. ePrints Soton (University of Southampton).14 indexed citations
18.
Cesa‐Bianchi, Nicolò. (2001). Potential-based Algorithms in On-line Prediction and Game Theory.
19.
Cesa‐Bianchi, Nicolò & Paul Fischer. (1998). Finite-Time Regret Bounds for the Multiarmed Bandit Problem. International Conference on Machine Learning. 100–108.31 indexed citations
20.
Cesa‐Bianchi, Nicolò. (1990). Learning the Distribution in the Extended PAC Model.. 236–246.2 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.