Amir Yehudayoff
- Computational Theory and Mathematics top 1%
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Discrete Mathematics and Combinatorics top 10%
- Topics
- Complexity and Algorithms in Graphs (41 papers)Advanced Graph Theory Research (16 papers)Machine Learning and Algorithms (14 papers)
- Cited by
- Computational Theory and MathematicsComputational MathematicsDiscrete Mathematics and Combinatorics
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Amir Yehudayoff
76 papers receiving 677 citations
Peers
Comparison fields: 5 of 67
- Computational Theory and Mathematics 514
- Artificial Intelligence 410
- Computer Networks and Communications 90
- Electrical and Electronic Engineering 74
- Discrete Mathematics and Combinatorics 54
Countries citing papers authored by Amir Yehudayoff
This map shows the geographic impact of Amir Yehudayoff'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 Amir Yehudayoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amir Yehudayoff more than expected).
Fields of papers citing papers by Amir Yehudayoff
This network shows the impact of papers produced by Amir Yehudayoff. 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 Amir Yehudayoff. The network helps show where Amir Yehudayoff may publish in the future.
Co-authorship network of co-authors of Amir Yehudayoff
This figure shows the co-authorship network connecting the top 25 collaborators of Amir Yehudayoff. A scholar is included among the top collaborators of Amir Yehudayoff 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 Amir Yehudayoff. Amir Yehudayoff is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 2 | |
| 5 | On Communication Complexity of Classification Problems | 1 |
| 6 | Supervised learning through the lens of compression | 5 |
| 7 | Proper PAC learning is compressing | 0 |
| 8 | Sign Rank, VC Dimension and Spectral Gaps | 2 |
| 9 | Inequalities and tail bounds for elementary symmetric polynomials. | 1 |
| 10 | Direct product via round-preserving compression. | 3 |
| 11 | 12 | |
| 12 | Direct Products in Communication Complexity. | 5 |
| 13 | Formulas are exponentially stronger than monotone circuits in non-commutative setting. | 1 |
| 14 | Linear cover time for trees is exponentially unlikely. | 0 |
| 15 | 6 | |
| 16 | 7 | |
| 17 | 9 | |
| 18 | Non-commutative circuits and the sum-of-squares problem. | 1 |
| 19 | Relationless completeness and separations. | 1 |
| 20 | Pseudorandomness for Width 2 Branching Programs. | 4 |
About Amir Yehudayoff
Amir Yehudayoff is a scholar working on Computational Theory and Mathematics, Discrete Mathematics and Combinatorics and Artificial Intelligence, having authored 88 papers that have together received 755 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (41 papers), Advanced Graph Theory Research (16 papers) and Machine Learning and Algorithms (14 papers). The work is most often cited by research in Computational Theory and Mathematics (514 citations), Computational Mathematics (19 citations) and Discrete Mathematics and Combinatorics (54 citations). Amir Yehudayoff has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Amir Shpilka, Ran Raz, Anup Rao, Pavel Hrubeš, Avi Wigderson, Shay Moran, Zeev Dvir, Mark Braverman, Omri Weinstein and Jean Bourgain. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the ACM and Machine Learning.
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.