Nicolò Cesa‐Bianchi
- Artificial Intelligence top 0.1%
- Management Science and Operations Research top 0.02%
- Computer Networks and Communications top 0.5%
- Electrical and Electronic Engineering top 5%
- Computer Vision and Pattern Recognition top 1%
- Co-authors
- Peter AuerPaul FischerGábor LugosiYoav FreundRobert E. SchapireClaudio GentileManfred K. WarmuthDavid Haussler
- Topics
- Machine Learning and Algorithms (72 papers)Advanced Bandit Algorithms Research (60 papers)Optimization and Search Problems (19 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceComputer Networks and Communications
- Partner nations
- ItalyUnited StatesSpain
In The Last Decade
Nicolò Cesa‐Bianchi
110 papers receiving 8.3k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Artificial Intelligence 5.5k
- Management Science and Operations Research 5.0k
- Computer Networks and Communications 2.4k
- Electrical and Electronic Engineering 1.2k
- Computer Vision and Pattern Recognition 694
Countries citing papers authored by Nicolò Cesa‐Bianchi
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.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | Cooperative Online Learning: Keeping your Neighbors Updated | 1 |
| 3 | Combining Cost-Sensitive Classification with Negative Selection for Protein Function Prediction. | 1 |
| 4 | Efficient second order online learning by sketching | 9 |
| 5 | Regret Minimization for Branching Experts | 2 |
| 6 | Random spanning trees and the prediction ofweighted graphs | 2 |
| 7 | Beyond Logarithmic Bounds in Online Learning | 8 |
| 8 | A Linear Time Active Learning Algorithm for Link Classification | 2 |
| 9 | A Correlation Clustering Approach to Link Classification in Signed Networks | 12 |
| 10 | Mirror descent meets fixed share (and feels no regret | 5 |
| 11 | Better Algorithms for Selective Sampling | 21 |
| 12 | 18 | |
| 13 | Fast and optimal prediction on a labeled tree | 19 |
| 14 | Linear Classification and Selective Sampling Under Low Noise Conditions | 16 |
| 15 | Worst-Case Analysis of Selective Sampling for Linear Classification | 65 |
| 16 | Improved risk tail bounds for on-line algorithms | 7 |
| 17 | Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms | 17 |
| 18 | Worst-Case Bounds for the Logarithmic Loss of Predictors | 1 |
| 19 | Finite-Time Regret Bounds for the Multiarmed Bandit Problem | 31 |
| 20 | Learning the Distribution in the Extended PAC Model. | 2 |
About Nicolò Cesa‐Bianchi
Nicolò Cesa‐Bianchi is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computational Theory and Mathematics, having authored 113 papers that have together received 8.8k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (72 papers), Advanced Bandit Algorithms Research (60 papers) and Optimization and Search Problems (19 papers). The work is most often cited by research in Management Science and Operations Research (5.0k citations), Artificial Intelligence (5.5k citations) and Computer Networks and Communications (2.4k citations). Nicolò Cesa‐Bianchi has collaborated with scholars based in Italy, United States and Spain. Frequent co-authors include Peter Auer, Paul Fischer, Gábor Lugosi, Yoav Freund, Robert E. Schapire, Claudio Gentile, Manfred K. Warmuth, David Haussler, Alex Conconi and David P. Helmbold. Their work appears in journals such as Bioinformatics, Econometrica and IEEE Transactions on Information Theory.
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.