Cyril Zhang

417 total citations
6 papers, 16 citations indexed

About

Cyril Zhang is a scholar working on Computational Mechanics, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Cyril Zhang has authored 6 papers receiving a total of 16 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computational Mechanics, 2 papers in Artificial Intelligence and 2 papers in Computational Theory and Mathematics. Recurrent topics in Cyril Zhang's work include Sparse and Compressive Sensing Techniques (3 papers), Markov Chains and Monte Carlo Methods (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). Cyril Zhang is often cited by papers focused on Sparse and Compressive Sensing Techniques (3 papers), Markov Chains and Monte Carlo Methods (2 papers) and Stochastic Gradient Optimization Techniques (2 papers). Cyril Zhang collaborates with scholars based in United States. Cyril Zhang's co-authors include Elad Hazan, Karan Singh, Karan Singh, Yi Zhang, Sanjeev Arora, Naman Agarwal, Brian Bullins, Danielle Bragg, Yi Zhang and Xinyi Chen and has published in prestigious journals such as arXiv (Cornell University), International Conference on Machine Learning and International Conference on Learning Representations.

In The Last Decade

Cyril Zhang

5 papers receiving 13 citations

Peers

Cyril Zhang
Zhaomin Xiao United States
Denis Teplyashin United Kingdom
Jakub Sygnowski United Kingdom
Pranav Shyam Switzerland
J. Lou China
Zhaomin Xiao United States
Cyril Zhang
Citations per year, relative to Cyril Zhang Cyril Zhang (= 1×) peers Zhaomin Xiao

Countries citing papers authored by Cyril Zhang

Since Specialization
Citations

This map shows the geographic impact of Cyril Zhang'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 Cyril Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cyril Zhang more than expected).

Fields of papers citing papers by Cyril Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cyril Zhang. 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 Cyril Zhang. The network helps show where Cyril Zhang may publish in the future.

Co-authorship network of co-authors of Cyril Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Cyril Zhang. A scholar is included among the top collaborators of Cyril Zhang 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 Cyril Zhang. Cyril Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
1.
Daumé, Hal, et al.. (2024). ASL STEM Wiki: Dataset and Benchmark for Interpreting STEM Articles. 14474–14490. 2 indexed citations
2.
Agarwal, Naman, Rohan Anil, Elad Hazan, Tomer Koren, & Cyril Zhang. (2019). Revisiting the Generalization of Adaptive Gradient Methods. 2 indexed citations
3.
Arora, Sanjeev, et al.. (2018). Towards Provable Control for Unknown Linear Dynamical Systems. International Conference on Learning Representations. 4 indexed citations
4.
Agarwal, Naman, Brian Bullins, Xinyi Chen, et al.. (2018). The Case for Full-Matrix Adaptive Regularization. arXiv (Cornell University).
5.
Agarwal, Naman, Brian Bullins, Xinyi Chen, et al.. (2018). Efficient Full-Matrix Adaptive Regularization. arXiv (Cornell University). 102–110. 2 indexed citations
6.
Hazan, Elad, Karan Singh, & Cyril Zhang. (2017). Efficient Regret Minimization in Non-Convex Games. International Conference on Machine Learning. 1433–1441. 6 indexed citations

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.

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