Aryan Mokhtari
About
In The Last Decade
Aryan Mokhtari
56 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 814
- Computer Networks and Communications 536
- Computational Mechanics 415
- Electrical and Electronic Engineering 215
- Numerical Analysis 150
Countries citing papers authored by Aryan Mokhtari
This map shows the geographic impact of Aryan Mokhtari'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 Aryan Mokhtari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aryan Mokhtari more than expected).
Fields of papers citing papers by Aryan Mokhtari
This network shows the impact of papers produced by Aryan Mokhtari. 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 Aryan Mokhtari. The network helps show where Aryan Mokhtari may publish in the future.
Co-authorship network of co-authors of Aryan Mokhtari
This figure shows the co-authorship network connecting the top 25 collaborators of Aryan Mokhtari. A scholar is included among the top collaborators of Aryan Mokhtari 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 Aryan Mokhtari. Aryan Mokhtari is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | Personalized Federated Learning with Theoretical Guarantees: A Model-Agnostic Meta-Learning Approach breakdown → | 266 |
| 4 | Quantized Push-sum for Gossip and Decentralized Optimization over Directed Graphs. | 3 |
| 5 | One Sample Stochastic Frank-Wolfe. | 2 |
| 6 | On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms | 12 |
| 7 | DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence Rate | 6 |
| 8 | A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach. | 18 |
| 9 | Stochastic Continuous Greedy ++: When Upper and Lower Bounds Match | 1 |
| 10 | Proximal Point Approximations Achieving a Convergence Rate of O(1/k) for Smooth Convex-Concave Saddle Point Problems: Optimistic Gradient and Extra-gradient Methods. | 2 |
| 11 | Quantized Frank-Wolfe: Communication-Efficient Distributed Optimization. | 2 |
| 12 | FedPAQ: A Communication-Efficient Federated Learning Method with Periodic Averaging and Quantization. | 48 |
| 13 | Direct runge-kutta discretization achieves acceleration | 4 |
| 14 | 9 | |
| 15 | A Second Order Method for Nonconvex Optimization | 0 |
| 16 | 1 | |
| 17 | 2 | |
| 18 | 72 | |
| 19 | 6 | |
| 20 | Network Newton | 7 |
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.