Cun Mu

904 total citations · 1 hit paper
8 papers, 555 citations indexed

About

Cun Mu is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition and Computational Mathematics. According to data from OpenAlex, Cun Mu has authored 8 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computational Mechanics, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Computational Mathematics. Recurrent topics in Cun Mu's work include Sparse and Compressive Sensing Techniques (3 papers), Tensor decomposition and applications (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Cun Mu is often cited by papers focused on Sparse and Compressive Sensing Techniques (3 papers), Tensor decomposition and applications (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). Cun Mu collaborates with scholars based in United States, Hong Kong and China. Cun Mu's co-authors include Wei Liu, Shih‐Fu Chang, Sanjiv Kumar, Donald Goldfarb, John Wright, Bo Huang, Yuqian Zhang, Shiqian Ma, John Smith and Rongrong Ji and has published in prestigious journals such as SIAM Journal on Scientific Computing, SIAM Journal on Matrix Analysis and Applications and Computational Optimization and Applications.

In The Last Decade

Cun Mu

7 papers receiving 543 citations

Hit Papers

align trajectories

What are hit papers?

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.

Discrete Graph Hashing

2014 331 citations Wei Liu, Cun Mu et al. Neural Information Processing Systems profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Cun Mu United States	6	414	164	126	91	50	8	555
Zhen Long China	10	193 0.5×	207 1.3×	213 1.7×	97 1.1×	52 1.0×	20	436
Changbo Zhu United States	8	102 0.2×	118 0.7×	26 0.2×	64 0.7×	39 0.8×	14	291
Gui‐Fu Lu China	11	300 0.7×	106 0.6×	26 0.2×	105 1.2×	39 0.8×	37	372
Mariya Ishteva Belgium	9	41 0.1×	98 0.6×	175 1.4×	52 0.6×	51 1.0×	26	301
Nigel Boston United States	14	93 0.2×	61 0.4×	16 0.1×	135 1.5×	49 1.0×	75	535
Zhening Li United Kingdom	12	22 0.1×	127 0.8×	255 2.0×	42 0.5×	54 1.1×	28	444
Yohann de Castro France	8	89 0.2×	220 1.3×	6 0.0×	52 0.6×	68 1.4×	24	347
Vassilis Kalofolias Switzerland	5	72 0.2×	63 0.4×	12 0.1×	113 1.2×	25 0.5×	6	207
In-So Kweon South Korea	5	267 0.6×	18 0.1×	17 0.1×	60 0.7×	50 1.0×	7	315
Max Simchowitz United States	6	69 0.2×	148 0.9×	11 0.1×	140 1.5×	25 0.5×	18	326

Countries citing papers authored by Cun Mu

Since Specialization

Citations

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

Fields of papers citing papers by Cun Mu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cun Mu

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Kang, Changsung, et al.. (2025). Large Scale Deployment of BERT Based Cross Encoder Model for Re-Ranking in Walmart Search Engine. 4365–4369.

2.

Mu, Cun, Daniel Hsu, & Donald Goldfarb. (2017). Greedy Approaches to Symmetric Orthogonal Tensor Decomposition. SIAM Journal on Matrix Analysis and Applications. 38(4). 1210–1226. 6 indexed citations

3.

Goldfarb, Donald, et al.. (2017). Using negative curvature in solving nonlinear programs. Computational Optimization and Applications. 68(3). 479–502. 6 indexed citations

4.

Mu, Cun, Yuqian Zhang, John Wright, & Donald Goldfarb. (2016). Scalable Robust Matrix Recovery: Frank--Wolfe Meets Proximal Methods. SIAM Journal on Scientific Computing. 38(5). A3291–A3317. 34 indexed citations

5.

Liu, Wei, Cun Mu, Rongrong Ji, et al.. (2015). Low-Rank Similarity Metric Learning in High Dimensions. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 31 indexed citations

6.

Liu, Wei, Cun Mu, Sanjiv Kumar, & Shih‐Fu Chang. (2014). Discrete Graph Hashing. Neural Information Processing Systems. 27. 3419–3427. 331 indexed citations breakdown →

7.

Mu, Cun, Bo Huang, John Wright, & Donald Goldfarb. (2013). Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery. arXiv (Cornell University). 73–81. 143 indexed citations

8.

Zhang, Yuqian, et al.. (2013). Toward Guaranteed Illumination Models for Non-convex Objects. 937–944. 4 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.

Explore authors with similar magnitude of impact