Yossi Arjevani
About
In The Last Decade
Yossi Arjevani
9 papers receiving 72 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 51
- Computational Mechanics 32
- Computer Networks and Communications 20
- Numerical Analysis 9
- Computational Theory and Mathematics 7
Countries citing papers authored by Yossi Arjevani
This map shows the geographic impact of Yossi Arjevani'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 Yossi Arjevani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yossi Arjevani more than expected).
Fields of papers citing papers by Yossi Arjevani
This network shows the impact of papers produced by Yossi Arjevani. 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 Yossi Arjevani. The network helps show where Yossi Arjevani may publish in the future.
Co-authorship network of co-authors of Yossi Arjevani
This figure shows the co-authorship network connecting the top 25 collaborators of Yossi Arjevani. A scholar is included among the top collaborators of Yossi Arjevani 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 Yossi Arjevani. Yossi Arjevani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 35 | |
| 2 | 2 | |
| 3 | Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry | 1 |
| 4 | IDEAL: Inexact decentralized accelerated augmented Lagrangian method | 1 |
| 5 | A Tight Convergence Analysis for Stochastic Gradient Descent with Delayed Updates | 1 |
| 6 | Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization | 3 |
| 7 | On lower and upper bounds in smooth and strongly convex optimization | 7 |
| 8 | On the iteration complexity of oblivious first-order optimization algorithms | 1 |
| 9 | 1 | |
| 10 | Communication complexity of distributed convex learning and optimization | 25 |
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.