Jarvis Haupt
- Computational Mechanics top 0.1%
- Sparse and Compressive Sensing Techniques 57
- Signal Processing top 0.5%
- Blind Source Separation Techniques 17
- Acoustics and Ultrasonics top 2%
- Computational Mathematics top 2%
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- Distributed Sensor Networks and Detection Algorithms 21
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- Microwave Imaging and Scattering Analysis 17
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- Indoor and Outdoor Localization Technologies 7
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- Stochastic Gradient Optimization Techniques 6
- Machine Learning and Algorithms 4
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- Image and Signal Denoising Methods 4
- Co-authors
- Robert D. NowakWaheed U. BajwaA.M. SayeedGil RazMichael RabbatArvind GaneshJosé Antonio UrigüenWeiyu Xu
- Journals
- Proceedings of the IEEE (1 paper)IEEE Transactions on Information Theory (6 papers)IEEE Transactions on Signal Processing (3 papers)
- Partner nations
- United StatesNetherlandsCanada
In The Last Decade
Jarvis Haupt
73 papers receiving 4.6k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Computational Mechanics 3.2k
- Signal Processing 1.1k
- Acoustics and Ultrasonics 91
- Computational Mathematics 51
- Computer Networks and Communications 1.2k
Countries citing papers authored by Jarvis Haupt
This map shows the geographic impact of Jarvis Haupt'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 Jarvis Haupt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jarvis Haupt more than expected).
Fields of papers citing papers by Jarvis Haupt
This network shows the impact of papers produced by Jarvis Haupt. 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 Jarvis Haupt. The network helps show where Jarvis Haupt may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jarvis Haupt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 5 | |
| 2 | A dictionary-based generalization of robust PCA Part I: Study of theoretical properties | 2019 | 1 |
| 3 | On Constrained Nonconvex Stochastic Optimization: A Case Study for Generalized Eigenvalue Decomposition | 2019 | 3 |
| 4 | 2019 | 3 | |
| 5 | 2017 | 2 | |
| 6 | On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning | 2017 | 6 |
| 7 | 2015 | 3 | |
| 8 | 2015 | 4 | |
| 9 | 2015 | 0 | |
| 10 | 2014 | 5 | |
| 11 | 2014 | 5 | |
| 12 | 2013 | 7 | |
| 13 | Compressed Sensingbreakdown → | 2012 | 1142 |
| 14 | Compressed Channel Sensing: A New Approach to Estimating Sparse Multipath Channels High-rate wireless data communication can usually be achieved by collecting a relatively small sample of the available information about the communications channel. | 2010 | 1 |
| 15 | Distilled sensing : selective sampling for sparse signal recovery | 2009 | 26 |
| 16 | 2008 | 53 | |
| 17 | 2007 | 211 | |
| 18 | 2006 | 8 | |
| 19 | 2006 | 231 | |
| 20 | 2006 | 2 |
About Jarvis Haupt
Jarvis Haupt is a scholar working on Computational Mathematics, Computational Mechanics and Signal Processing, having authored 74 papers that have together received 4.8k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (57 papers), Distributed Sensor Networks and Detection Algorithms (21 papers), Blind Source Separation Techniques (17 papers), Microwave Imaging and Scattering Analysis (17 papers), Indoor and Outdoor Localization Technologies (7 papers), Stochastic Gradient Optimization Techniques (6 papers), Machine Learning and Algorithms (4 papers) and Image and Signal Denoising Methods (4 papers). The work is most often cited by research in Computational Mechanics (3.2k citations), Signal Processing (1.1k citations) and Acoustics and Ultrasonics (91 citations). Jarvis Haupt has collaborated with scholars based in United States, Netherlands and Canada. Frequent co-authors include Robert D. Nowak, Waheed U. Bajwa, A.M. Sayeed, Gil Raz, Michael Rabbat, Arvind Ganesh, José Antonio Urigüen, Weiyu Xu, Robert Calderbank and Gitta Kutyniok. Their work appears in journals such as Proceedings of the IEEE, IEEE Transactions on Information Theory and IEEE Transactions on Signal Processing.
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.