Dongruo Zhou
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Computational Mechanics
- Statistical and Nonlinear Physics
- Electrical and Electronic Engineering
- Topics
- Sparse and Compressive Sensing Techniques (7 papers)Stochastic Gradient Optimization Techniques (7 papers)Advanced Neural Network Applications (3 papers)
- Journals
- Machine LearningJournal of Machine Learning ResearcharXiv (Cornell University)
- Partner nations
- United StatesCanada
In The Last Decade
Dongruo Zhou
10 papers receiving 198 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 150
- Computer Vision and Pattern Recognition 49
- Computational Mechanics 48
- Statistical and Nonlinear Physics 22
- Electrical and Electronic Engineering 21
Countries citing papers authored by Dongruo Zhou
This map shows the geographic impact of Dongruo Zhou'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 Dongruo Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dongruo Zhou more than expected).
Fields of papers citing papers by Dongruo Zhou
This network shows the impact of papers produced by Dongruo Zhou. 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 Dongruo Zhou. The network helps show where Dongruo Zhou may publish in the future.
Co-authorship network of co-authors of Dongruo Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Dongruo Zhou. A scholar is included among the top collaborators of Dongruo Zhou 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 Dongruo Zhou. Dongruo Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Accelerated Factored Gradient Descent for Low-Rank Matrix Factorization | 2 |
| 2 | 18 | |
| 3 | 30 | |
| 4 | 121 | |
| 5 | Neural Contextual Bandits with Upper Confidence Bound-Based Exploration | 3 |
| 6 | Lower Bounds for Smooth Nonconvex Finite-Sum Optimization | 1 |
| 7 | Stochastic Variance-Reduced Cubic Regularization Methods | 5 |
| 8 | Stochastic Variance-Reduced Cubic Regularized Newton Methods | 7 |
| 9 | Stochastic Nested Variance Reduced Gradient Descent for Nonconvex Optimization. | 11 |
| 10 | Stochastic Nested Variance Reduction for Nonconvex Optimization | 10 |
About Dongruo Zhou
Dongruo Zhou is a scholar working on Computational Mechanics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 10 papers that have together received 208 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (7 papers), Stochastic Gradient Optimization Techniques (7 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computational Mathematics (3 citations), Artificial Intelligence (150 citations) and Computer Vision and Pattern Recognition (49 citations). Dongruo Zhou has collaborated with scholars based in United States and Canada. Frequent co-authors include Quanquan Gu, Yuan Cao, Difan Zou, Pan Xu, Jinghui Chen, Jinfeng Yi, Ziyan Yang, Yuan Cao and Lihong Li. Their work appears in journals such as Machine Learning, Journal of Machine Learning Research and arXiv (Cornell University).
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.