Christopher Musco

1.3k total citations
26 papers, 415 citations indexed

About

Christopher Musco is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Christopher Musco has authored 26 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 8 papers in Computational Theory and Mathematics and 7 papers in Computational Mechanics. Recurrent topics in Christopher Musco's work include Stochastic Gradient Optimization Techniques (9 papers), Sparse and Compressive Sensing Techniques (6 papers) and Data Management and Algorithms (5 papers). Christopher Musco is often cited by papers focused on Stochastic Gradient Optimization Techniques (9 papers), Sparse and Compressive Sensing Techniques (6 papers) and Data Management and Algorithms (5 papers). Christopher Musco collaborates with scholars based in United States, Australia and Switzerland. Christopher Musco's co-authors include Cameron Musco, Michael B. Cohen, Juliana Freire, Michael Kapralov, Fernando Chirigati, Yin Tat Lee, Aaron Sidford, Stelios Sidiroglou-Douskos, Brendan Juba and Martin Rinard and has published in prestigious journals such as Proceedings of the VLDB Endowment, Computer Graphics Forum and SIAM Journal on Matrix Analysis and Applications.

In The Last Decade

Christopher Musco

24 papers receiving 397 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Christopher Musco United States 11 222 84 81 66 60 26 415
Michael Kapralov United States 15 213 1.0× 106 1.3× 86 1.1× 197 3.0× 158 2.6× 34 462
Takanori Maehara Japan 15 298 1.3× 104 1.2× 19 0.2× 68 1.0× 92 1.5× 49 535
Aditya Bhaskara United States 9 156 0.7× 51 0.6× 39 0.5× 175 2.7× 107 1.8× 38 397
Eunho Yang South Korea 15 405 1.8× 136 1.6× 65 0.8× 44 0.7× 21 0.3× 74 691
Maria Florina Balcan United States 10 210 0.9× 107 1.3× 17 0.2× 40 0.6× 25 0.4× 17 361
Yuanyuan Zhu China 12 139 0.6× 112 1.3× 26 0.3× 63 1.0× 85 1.4× 60 409
Kai-Yang Chiang United States 8 298 1.3× 70 0.8× 84 1.0× 13 0.2× 43 0.7× 9 465
Aiyou Chen United States 9 225 1.0× 45 0.5× 22 0.3× 47 0.7× 80 1.3× 19 623
Alexander Ivrii United States 9 268 1.2× 91 1.1× 11 0.1× 113 1.7× 49 0.8× 21 477
Samantha Hansen United States 4 244 1.1× 54 0.6× 111 1.4× 33 0.5× 23 0.4× 6 392

Countries citing papers authored by Christopher Musco

Since Specialization
Citations

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

Fields of papers citing papers by Christopher Musco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher Musco

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

All Works

20 of 20 papers shown
1.
Freire, Juliana, et al.. (2024). Sampling Methods for Inner Product Sketching. Proceedings of the VLDB Endowment. 17(9). 2185–2197. 3 indexed citations
2.
Stoyanovich, Julia, et al.. (2024). A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. Proceedings of the AAAI Conference on Artificial Intelligence. 38(19). 21554–21562. 1 indexed citations
3.
4.
Freire, Juliana, et al.. (2023). Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. 169–181. 2 indexed citations
5.
Musco, Cameron, Christopher Musco, David P. Woodruff, & Taisuke Yasuda. (2022). Active Linear Regression for ℓp Norms and Beyond. 38. 744–753. 4 indexed citations
6.
Chiang, Yi‐Jen, et al.. (2022). Streaming Approach to In Situ Selection of Key Time Steps for Time‐Varying Volume Data. Computer Graphics Forum. 41(3). 309–320. 1 indexed citations
7.
Greenbaum, Anne, et al.. (2022). Error Bounds for Lanczos-Based Matrix Function Approximation. SIAM Journal on Matrix Analysis and Applications. 43(2). 787–811. 6 indexed citations
8.
Wang, Sheng, Yuan Sun, Christopher Musco, & Zhifeng Bao. (2021). Public Transport Planning: When Transit Network Connectivity Meets Commuting Demand. Figshare. 1 indexed citations
9.
Wang, Sheng, Yuan Sun, Christopher Musco, & Zhifeng Bao. (2021). Public Transport Planning. arXiv (Cornell University). 1906–1919. 14 indexed citations
10.
Chirigati, Fernando, et al.. (2021). Correlation Sketches for Approximate Join-Correlation Queries. arXiv (Cornell University). 1531–1544. 30 indexed citations
11.
Musco, Christopher, et al.. (2020). Analyzing the Impact of Filter Bubbles on Social Network Polarization. 115–123. 70 indexed citations
12.
Mallmann-Trenn, Frederik, Cameron Musco, & Christopher Musco. (2018). Eigenvector Computation and Community Detection in Asynchronous Gossip\n Models. arXiv (Cornell University). 2 indexed citations
13.
Hoskins, Jeremy G., Cameron Musco, Christopher Musco, & Charalampos E. Tsourakakis. (2018). Inferring Networks From Random Walk-Based Node Similarities. neural information processing systems. 31. 3704–3715. 1 indexed citations
14.
Cohen, Michael B., Cameron Musco, & Christopher Musco. (2017). Input sparsity time low-rank approximation via ridge leverage score sampling. Symposium on Discrete Algorithms. 1758–1777. 18 indexed citations
15.
Avron, Haim, et al.. (2017). Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. International Conference on Machine Learning. 253–262. 15 indexed citations
16.
Musco, Cameron & Christopher Musco. (2017). Recursive Sampling for the Nyström Method. arXiv (Cornell University). 30. 3834–3846. 24 indexed citations
17.
Musco, Cameron & Christopher Musco. (2015). Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods.. arXiv (Cornell University). 4 indexed citations
18.
Musco, Cameron & Christopher Musco. (2015). Stronger and Faster Approximate Singular Value Decomposition via the Block Lanczos Method. arXiv (Cornell University). 3 indexed citations
19.
Juba, Brendan, Christopher Musco, Fan Long, Stelios Sidiroglou-Douskos, & Martin Rinard. (2015). Principled Sampling for Anomaly Detection. 18 indexed citations
20.
Cohen, Michael B., et al.. (2015). Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. 163–172. 128 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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