Roi Livni
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Computational Mechanics
- Management Science and Operations Research
- Co-authors
- Shai Shalev‐ShwartzOhad ShamirShay MoranAmir GlobersonPierre SimonMark BunYishay MansourElad Hazan
- Topics
- Machine Learning and Algorithms (10 papers)Advanced Bandit Algorithms Research (6 papers)Neural Networks and Applications (3 papers)
- Journals
- Journal of the ACMJournal of Machine Learning ResearchExtracta Mathematicae
- Partner nations
- IsraelUnited StatesIndia
In The Last Decade
Roi Livni
15 papers receiving 177 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 116
- Computer Vision and Pattern Recognition 48
- Computational Theory and Mathematics 25
- Computational Mechanics 20
- Management Science and Operations Research 17
Countries citing papers authored by Roi Livni
This map shows the geographic impact of Roi Livni'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 Roi Livni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roi Livni more than expected).
Fields of papers citing papers by Roi Livni
This network shows the impact of papers produced by Roi Livni. 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 Roi Livni. The network helps show where Roi Livni may publish in the future.
Co-authorship network of co-authors of Roi Livni
This figure shows the co-authorship network connecting the top 25 collaborators of Roi Livni. A scholar is included among the top collaborators of Roi Livni 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 Roi Livni. Roi Livni 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 | A Limitation of the PAC-Bayes Framework | 1 |
| 3 | 11 | |
| 4 | Passing Tests without Memorizing: Two Models for Fooling Discriminators. | 1 |
| 5 | On Communication Complexity of Classification Problems | 1 |
| 6 | Effective Semisupervised Learning on Manifolds | 3 |
| 7 | Affine-Invariant Online Optimization and the Low-rank Experts Problem | 1 |
| 8 | 0 | |
| 9 | Improper Deep Kernels | 0 |
| 10 | Online pricing with strategic and patient buyers | 4 |
| 11 | 7 | |
| 12 | On the Computational Efficiency of Training Neural Networks | 109 |
| 13 | 8 | |
| 14 | A Provably Efficient Algorithm for Training Deep Networks | 12 |
| 15 | Vanishing Component Analysis | 18 |
| 16 | A Simple Geometric Interpretation of SVM using Stochastic Adversaries | 4 |
| 17 | On extreme points of the dual ball of a polyhedral space | 3 |
About Roi Livni
Roi Livni is a scholar working on Computational Mathematics, Management Science and Operations Research and Artificial Intelligence, having authored 17 papers that have together received 187 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (10 papers), Advanced Bandit Algorithms Research (6 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Computational Mathematics (5 citations), Artificial Intelligence (116 citations) and Computer Vision and Pattern Recognition (48 citations). Roi Livni has collaborated with scholars based in Israel, United States and India. Frequent co-authors include Shai Shalev‐Shwartz, Ohad Shamir, Shay Moran, Amir Globerson, Pierre Simon, Mark Bun, Yishay Mansour, Elad Hazan, Koby Crammer and Aviv Zohar. Their work appears in journals such as Journal of the ACM, Journal of Machine Learning Research and Extracta Mathematicae.
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.