Anna Ma

457 total citations
24 papers, 241 citations indexed

About

Anna Ma is a scholar working on Computational Mechanics, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Anna Ma has authored 24 papers receiving a total of 241 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computational Mechanics, 11 papers in Artificial Intelligence and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Anna Ma's work include Sparse and Compressive Sensing Techniques (18 papers), Stochastic Gradient Optimization Techniques (9 papers) and Blind Source Separation Techniques (5 papers). Anna Ma is often cited by papers focused on Sparse and Compressive Sensing Techniques (18 papers), Stochastic Gradient Optimization Techniques (9 papers) and Blind Source Separation Techniques (5 papers). Anna Ma collaborates with scholars based in United States, United Kingdom and Morocco. Anna Ma's co-authors include Deanna Needell, Aaditya Ramdas, Cynthia Rush, Dror Baron, Andrea L. Bertozzi, Yves van Gennip, Daniel Moyer, You Zhou, Arjuna Flenner and Jing Qin and has published in prestigious journals such as IEEE Transactions on Signal Processing, SIAM Journal on Matrix Analysis and Applications and Applied and Computational Harmonic Analysis.

In The Last Decade

Anna Ma

21 papers receiving 227 citations

Peers

Anna Ma

CM

AI

CTM

NA

CM

Wen-Ting Wu China

Pavel Dvurechensky Russia

Brian Bullins United States

Dennis Amelunxen Germany

Petar Maymounkov United States

Adi Shraibman Israel

John P. May United States

Masayuki Noro Japan

Matt Menickelly United States

Khalide Jbilou France

Wen-Ting Wu China

Anna Ma

368 ×2.2

CM

328 ×2.3

AI

241 ×2.7

CTM

168 ×3.7

NA

21 ×0.8

CM

Citations per year, relative to Anna Ma Anna Ma (= 1×) peers Wen-Ting Wu

Countries citing papers authored by Anna Ma

Since Specialization

Citations

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

Fields of papers citing papers by Anna Ma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Ma

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

All Works

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20 of 20 papers shown

1.

Ma, Anna, et al.. (2025). Reverse Quantile‐RK and Its Application to Quantile‐RK. Numerical Linear Algebra with Applications. 32(3).

2.

Bergou, El Houcine, et al.. (2024). A Note on the Randomized Kaczmarz Algorithm for Solving Doubly Noisy Linear Systems. SIAM Journal on Matrix Analysis and Applications. 45(2). 992–1006. 1 indexed citations

3.

Li, Shuang, et al.. (2024). Iterative singular tube hard thresholding algorithms for tensor recovery. Inverse Problems and Imaging. 18(4). 889–907.

4.

Ma, Anna, et al.. (2023). Block-missing data in linear systems: An unbiased stochastic gradient descent approach. 12. 1–7. 1 indexed citations

5.

Ma, Anna, et al.. (2023). Robust Recovery of Low-Rank Matrices and Low-Tubal-Rank Tensors from Noisy Sketches. SIAM Journal on Matrix Analysis and Applications. 44(4). 1566–1588. 1 indexed citations

6.

Ma, Anna, et al.. (2023). On Subsampled Quantile Randomized Kaczmarz. 1–8. 2 indexed citations

7.

Ma, Anna, et al.. (2021). Randomized Kaczmarz for tensor linear systems. BIT Numerical Mathematics. 62(1). 171–194. 23 indexed citations

8.

Ma, Anna, et al.. (2021). On the number of faces and radii of cells induced by Gaussian spherical tessellations. Applied and Computational Harmonic Analysis. 56. 176–188. 2 indexed citations

9.

Ma, Anna, et al.. (2020). Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. 1–5. 2 indexed citations

10.

Loera, Jesús A. De, et al.. (2020). Data-driven algorithm selection and tuning in optimization and signal processing. Annals of Mathematics and Artificial Intelligence. 89(7). 711–735. 2 indexed citations

11.

Ma, Anna, You Zhou, Cynthia Rush, Dror Baron, & Deanna Needell. (2019). An Approximate Message Passing Framework for Side Information. IEEE Transactions on Signal Processing. 67(7). 1875–1888. 11 indexed citations

12.

Ravishankar, Saiprasad, Anna Ma, & Deanna Needell. (2019). Analysis of fast structured dictionary learning [Image: see text]. PubMed Central. 3 indexed citations

13.

Huang, Chenxi, et al.. (2019). Fast Hyperspectral Diffuse Optical Imaging Method with Joint Sparsity. PubMed. 2019. 4758–4761. 4 indexed citations

14.

Gennip, Yves van, et al.. (2018). Unsupervised record matching with noisy and incomplete data. International Journal of Data Science and Analytics. 6(2). 109–129. 9 indexed citations

15.

Ma, Anna, Deanna Needell, & Aaditya Ramdas. (2018). Iterative Methods for Solving Factorized Linear Systems. SIAM Journal on Matrix Analysis and Applications. 39(1). 104–122. 14 indexed citations

16.

Ma, Anna & Deanna Needell. (2017). Adapted Stochastic Gradient Descent for Linear Systems with Missing Data. arXiv (Cornell University). 2 indexed citations

17.

Baron, Dror, et al.. (2017). Conditional approximate message passing with side information. 106. 430–434. 3 indexed citations

18.

Ma, Anna, Deanna Needell, & Aaditya Ramdas. (2015). Convergence Properties of the Randomized Extended Gauss--Seidel and Kaczmarz Methods. SIAM Journal on Matrix Analysis and Applications. 36(4). 1590–1604. 120 indexed citations

19.

Ma, Anna, Arjuna Flenner, Deanna Needell, & Allon G. Percus. (2014). Improving image clustering using sparse text and the wisdom of the crowds. 2014 48th Asilomar Conference on Signals, Systems and Computers. 1555–1557. 2 indexed citations

20.

Tokarchuk, Laurissa, et al.. (2009). Using co-presence communities to enhance social recommendation. 169–172. 1 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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