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.
Probing the Pareto Frontier for Basis Pursuit Solutions
20081.3k citationsE. van den Berg, Michael P. FriedlanderSIAM Journal on Scientific Computingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Michael P. Friedlander
Since
Specialization
Citations
This map shows the geographic impact of Michael P. Friedlander'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 Michael P. Friedlander with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael P. Friedlander more than expected).
Fields of papers citing papers by Michael P. Friedlander
This network shows the impact of papers produced by Michael P. Friedlander. 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 Michael P. Friedlander. The network helps show where Michael P. Friedlander may publish in the future.
Co-authorship network of co-authors of Michael P. Friedlander
This figure shows the co-authorship network connecting the top 25 collaborators of Michael P. Friedlander.
A scholar is included among the top collaborators of Michael P. Friedlander 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 Michael P. Friedlander. Michael P. Friedlander is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Friedlander, Michael P., et al.. (2022). Polar Deconvolution of Mixed Signals. IEEE Transactions on Signal Processing. 70. 2713–2727.1 indexed citations
Huang, Fang, et al.. (2020). Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization.. International Conference on Artificial Intelligence and Statistics. 434–444.2 indexed citations
Huang, Fang, et al.. (2020). Online mirror descent and dual averaging: keeping pace in the dynamic case. International Conference on Machine Learning. 1. 3008–3017.2 indexed citations
Goh, Gabriel, Andrew Cotter, Maya R. Gupta, & Michael P. Friedlander. (2016). Satisfying real-world goals with dataset constraints. Neural Information Processing Systems. 29. 2423–2431.9 indexed citations
10.
Khan, Mohammad Emtiyaz, Aleksandr Y. Aravkin, Michael P. Friedlander, & Matthias Seeger. (2013). Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 951–959.12 indexed citations
11.
Friedlander, Michael P., et al.. (2013). Gauge optimization, duality, and applications. arXiv (Cornell University).1 indexed citations
Orban, Dominique & Michael P. Friedlander. (2010). A Primal-Dual Regularized Interior-Point Method for Convex Quadratic Programs. Les Cahiers du GERAD. 1–31.1 indexed citations
15.
Schmidt, Mark, E. van den Berg, Michael P. Friedlander, & Kevin P. Murphy. (2009). Optimizing Costly Functions with Simple Constraints: A Limited-Memory Projected Quasi-Newton Algorithm. International Conference on Artificial Intelligence and Statistics. 456–463.147 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.