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.
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
This map shows the geographic impact of Maryam Fazel'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 Maryam Fazel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maryam Fazel more than expected).
This network shows the impact of papers produced by Maryam Fazel. 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 Maryam Fazel. The network helps show where Maryam Fazel may publish in the future.
Co-authorship network of co-authors of Maryam Fazel
This figure shows the co-authorship network connecting the top 25 collaborators of Maryam Fazel.
A scholar is included among the top collaborators of Maryam Fazel 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 Maryam Fazel. Maryam Fazel is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Oymak, Samet, et al.. (2020). Finite Sample System Identification: Optimal Rates and the Role of Regularization.. 16–25.6 indexed citations
7.
Sun, Yue, Nicolas Flammarion, & Maryam Fazel. (2019). Escaping from saddle points on Riemannian manifolds. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 32. 7276–7286.2 indexed citations
8.
Jalali, Amin, et al.. (2016). Exploiting tradeoffs for exact recovery in heterogeneous stochastic block models. Neural Information Processing Systems. 29. 4871–4879.3 indexed citations
9.
Fazel, Maryam, et al.. (2016). Designing smoothing functions for improved worst-case competitive ratio in online optimization. Neural Information Processing Systems. 29. 3279–3287.9 indexed citations
10.
London, Palma, et al.. (2014). Node-Based Learning of Multiple Gaussian Graphical Models.. PubMed. 15(1). 445–488.93 indexed citations
11.
Arora, Raman, et al.. (2013). Similarity-based clustering by left-stochastic matrix factorization. Journal of Machine Learning Research. 14(1). 1715–1746.12 indexed citations
Arora, Raman, et al.. (2011). Clustering by Left-Stochastic Matrix Factorization. International Conference on Machine Learning. 761–768.18 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.