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.
Message-passing algorithms for compressed sensing
20091.5k citationsDavid L. Donoho, Arian Maleki et al.Proceedings of the National Academy of Sciencesprofile →
Compressed Sensing
20121.1k citationsAndrea Montanari et al.profile →
Countries citing papers authored by Andrea Montanari
Since
Specialization
Citations
This map shows the geographic impact of Andrea Montanari'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 Andrea Montanari with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea Montanari more than expected).
Fields of papers citing papers by Andrea Montanari
This network shows the impact of papers produced by Andrea Montanari. 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 Andrea Montanari. The network helps show where Andrea Montanari may publish in the future.
Co-authorship network of co-authors of Andrea Montanari
This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Montanari.
A scholar is included among the top collaborators of Andrea Montanari 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 Andrea Montanari. Andrea Montanari 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.
Chen, Cheng & Andrea Montanari. (2024). Dimension free ridge regression. The Annals of Statistics. 52(6).3 indexed citations
Song, Mei, Theodor Misiakiewicz, & Andrea Montanari. (2019). Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit. Conference on Learning Theory. 2388–2464.4 indexed citations
4.
Mondelli, Marco & Andrea Montanari. (2019). On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition. International Conference on Artificial Intelligence and Statistics. 1051–1060.7 indexed citations
5.
Ghorbani, Behrooz, Mei Song, Theodor Misiakiewicz, & Andrea Montanari. (2019). Limitations of Lazy Training of Two-layers Neural Network. Neural Information Processing Systems. 32. 9108–9118.16 indexed citations
Erdogdu, Murat A., Yash Deshpande, & Andrea Montanari. (2017). Inference in Graphical Models via Semidefinite Programming Hierarchies. Neural Information Processing Systems. 30. 417–425.1 indexed citations
9.
Abbé, Emmanuel & Andrea Montanari. (2015). . Theory of Computing. 11(1). 413–443.13 indexed citations
10.
Richard, Émile & Andrea Montanari. (2014). A statistical model for tensor PCA. Neural Information Processing Systems. 27. 2897–2905.32 indexed citations
11.
Deshpande, Yash, Andrea Montanari, & Émile Richard. (2014). Cone-Constrained Principal Component Analysis. Neural Information Processing Systems. 27. 2717–2725.12 indexed citations
12.
Bayati, Mohsen, Murat A. Erdogdu, & Andrea Montanari. (2013). Estimating LASSO Risk and Noise Level. Neural Information Processing Systems. 26. 944–952.23 indexed citations
13.
Javanmard, Adel & Andrea Montanari. (2013). Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models. Neural Information Processing Systems. 26. 1187–1195.8 indexed citations
14.
Deshpande, Yash & Andrea Montanari. (2012). Linear Bandits in High Dimension and Recommendation Systems.16 indexed citations
15.
Bayati, Mohsen, José Pereira, & Andrea Montanari. (2010). The LASSO risk: asymptotic results and real world examples. Neural Information Processing Systems. 23. 145–153.5 indexed citations
Donoho, David L., Arian Maleki, & Andrea Montanari. (2009). Message-passing algorithms for compressed sensing. Proceedings of the National Academy of Sciences. 106(45). 18914–18919.1479 indexed citations breakdown →
18.
Montanari, Andrea & José Pereira. (2009). Which graphical models are difficult to learn. Neural Information Processing Systems. 22. 1303–1311.20 indexed citations
19.
Méasson, Cyril, Andrea Montanari, & Rüdiger Urbanke. (2005). Maxwell Construction: The Hidden Bridge between Iterative and Maximum a Posteriori Decoding. ArXiv.org.10 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.