Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Sensitivity to Basis Mismatch in Compressed Sensing
2011627 citationsYuejie Chi, Ali Pezeshki et al.IEEE Transactions on Signal Processingprofile →
Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
2019216 citationsYuejie Chi, Yue M. Lu et al.IEEE Transactions on Signal Processingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Yuejie Chi'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 Yuejie Chi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuejie Chi more than expected).
This network shows the impact of papers produced by Yuejie Chi. 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 Yuejie Chi. The network helps show where Yuejie Chi may publish in the future.
Co-authorship network of co-authors of Yuejie Chi
This figure shows the co-authorship network connecting the top 25 collaborators of Yuejie Chi.
A scholar is included among the top collaborators of Yuejie Chi 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 Yuejie Chi. Yuejie Chi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Li, Gen, et al.. (2021). Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning. arXiv (Cornell University). 6296–6306.4 indexed citations
Chi, Yuejie, Yue M. Lu, & Yuxin Chen. (2019). Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview. IEEE Transactions on Signal Processing. 67(20). 5239–5269.216 indexed citations breakdown →
12.
Balzano, Laura, Yuejie Chi, & Yue M. Lu. (2018). A Modern Perspective on Streaming PCA and Subspace Tracking: The Missing Data Case. Proceedings of the IEEE. 106(8).1 indexed citations
13.
Vaswani, Namrata, Yuejie Chi, & Thierry Bouwmans. (2018). Rethinking PCA for Modern Data Sets: Theory, Algorithms, and Applications. Proceedings of the IEEE. 106. 1274–1276.8 indexed citations
14.
Zhang, Huishuai, Yingbin Liang, & Yuejie Chi. (2017). A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms. Journal of Machine Learning Research. 18(141). 1–35.53 indexed citations
Chi, Yuejie, et al.. (2009). Sensitivity to basis mismatch of compressed sensing for spectrum analysis and beamforming.13 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.