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.
Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems
20072.5k citationsMário A. T. Figueiredo, Robert D. Nowak et al.profile →
Sparse Reconstruction by Separable Approximation
20091.3k citationsRobert D. Nowak, Mário A. T. Figueiredo et al.profile →
Wavelet-based statistical signal processing using hidden Markov models
Countries citing papers authored by Robert D. Nowak
Since
Specialization
Citations
This map shows the geographic impact of Robert D. Nowak'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 Robert D. Nowak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert D. Nowak more than expected).
This network shows the impact of papers produced by Robert D. Nowak. 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 Robert D. Nowak. The network helps show where Robert D. Nowak may publish in the future.
Co-authorship network of co-authors of Robert D. Nowak
This figure shows the co-authorship network connecting the top 25 collaborators of Robert D. Nowak.
A scholar is included among the top collaborators of Robert D. Nowak 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 Robert D. Nowak. Robert D. Nowak is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Nowak, Robert D., et al.. (2021). Banach Space Representer Theorems for Neural Networks and Ridge Splines. Journal of Machine Learning Research. 22(43). 1–40.5 indexed citations
Nowak, Robert D., et al.. (2020). Neural Networks, Ridge Splines, and TV Regularization in the Radon Domain.. arXiv (Cornell University).2 indexed citations
5.
Jain, Lalit, et al.. (2017). Learning Low-Dimensional Metrics. Neural Information Processing Systems. 30. 4139–4147.1 indexed citations
6.
Nowak, Robert D., et al.. (2017). A KL-LUCB algorithm for Large-Scale Crowdsourcing. Neural Information Processing Systems. 30. 5894–5903.5 indexed citations
7.
Bhargava, Aniruddha, et al.. (2017). Active Positive Semidefinite Matrix Completion: Algorithms, Theory and Applications. International Conference on Artificial Intelligence and Statistics. 1349–1357.2 indexed citations
8.
Figueiredo, Mário A. T. & Robert D. Nowak. (2016). Ordered Weighted L1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects. International Conference on Artificial Intelligence and Statistics. 930–938.23 indexed citations
9.
Nowak, Robert D., et al.. (2016). The information-theoretic requirements of subspace clustering with missing data. International Conference on Machine Learning. 802–810.20 indexed citations
10.
Jun, Kwang-Sung, Kevin Jamieson, Robert D. Nowak, & Xiaojin Zhu. (2016). Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls. International Conference on Artificial Intelligence and Statistics. 139–148.6 indexed citations
11.
Rau, Martina A., et al.. (2016). How to Model Implicit Knowledge? Similarity Learning Methods to Assess Perceptions of Visual Representations.. Educational Data Mining. 199–206.7 indexed citations
12.
Dasarathy, Gautam, Robert D. Nowak, & Xiaojin Zhu. (2015). S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification. Journal of Machine Learning Research. 40(2015). 503–522.7 indexed citations
13.
Jamieson, Kevin, Matthew Malloy, Robert D. Nowak, & Sébastien Bubeck. (2014). lil' UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits. Conference on Learning Theory. 423–439.40 indexed citations
14.
Rao, Nikhil, Benjamin Recht, & Robert D. Nowak. (2012). Universal Measurement Bounds for Structured Sparse Signal Recovery. International Conference on Artificial Intelligence and Statistics. 942–950.23 indexed citations
15.
Goldberg, Andrew B., Ben Recht, Junming Xu, Robert D. Nowak, & Xiaojin Zhu. (2010). Transduction with Matrix Completion: Three Birds with One Stone. Neural Information Processing Systems. 23. 757–765.132 indexed citations
16.
Haupt, Jarvis, Rui Castro, & Robert D. Nowak. (2009). Distilled sensing : selective sampling for sparse signal recovery. TU/e Research Portal. 5. 216–223.26 indexed citations
17.
Singh, Aarti, Robert D. Nowak, & Xiaojin Zhu. (2008). Unlabeled data: Now it helps, now it doesn't. Neural Information Processing Systems. 21. 1513–1520.116 indexed citations
18.
Willett, Rebecca, Ian H. Jermyn, Robert D. Nowak, & Josiane Zerubia. (2003). Wavelet-Based Superresolution in Astronomy. Durham Research Online (Durham University). 314. 107.7 indexed citations
19.
Willett, Rebecca, Robert D. Nowak, & Eric D. Kolaczyk. (2002). Multiscale Analysis of Photon-Limited Astronomical Signals and Images. AAS. 201.1 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.