Benjamin Recht
Impact in
- Computational Mathematics top 0.05%
- Tensor decomposition and applications
- Computational Mechanics top 0.05%
- Sparse and Compressive Sensing Techniques
Papers in
-
- Sparse and Compressive Sensing Techniques 39
-
- Stochastic Gradient Optimization Techniques 9
- Machine Learning and Algorithms 8
- Co-authors
- Emmanuel J. Candès (6 shared papers)Ali Rahimi (3 shared papers)Pablo A. Parrilo (5 shared papers)Maryam Fazel (3 shared papers)Badri Narayan Bhaskar (9 shared papers)Gongguo Tang (9 shared papers)Moritz Hardt (6 shared papers)Christopher Ré (4 shared papers)
- Journals
- IEEE Transactions on Information Theory (4 papers)Mathematical Programming (3 papers)Foundations of Computational Mathematics (2 papers)Communications of the ACM (2 papers)PLoS ONE (2 papers)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Benjamin Recht
100 papers receiving 15.8k citations
Benjamin Recht's Hit Papers
Peers
Comparison fields: 5 of 198
- Computational Mathematics 996
- Computational Mechanics 6.8k
- Computer Vision and Pattern Recognition 5.0k
- Signal Processing 2.6k
- Computer Graphics and Computer-Aided Design 608
Countries citing papers authored by Benjamin Recht
This map shows the geographic impact of Benjamin Recht'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 Benjamin Recht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin Recht more than expected).
Fields of papers citing papers by Benjamin Recht
This network shows the impact of papers produced by Benjamin Recht. 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 Benjamin Recht. The network helps show where Benjamin Recht may publish in the future.
Co-authors
The 25 scholars most cited alongside Benjamin Recht, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 101 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Exact Matrix Completion via Convex Optimization Hit paper breakdown → | 2009 | 3128 |
| 2 | Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization Hit paper breakdown → | 2010 | 2114 |
| 3 | Understanding deep learning (still) requires rethinking generalization Hit paper breakdown → | 2021 | 1317 |
| 4 | Random Features for Large-Scale Kernel Machines Hit paper breakdown → | 2007 | 1267 |
| 5 | Compressed Sensing Off the Grid Hit paper breakdown → | 2013 | 780 |
| 6 | Plenoxels: Radiance Fields without Neural Networks Hit paper breakdown → | 2022 | 735 |
| 7 | Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Hit paper breakdown → | 2011 | 659 |
| 8 | Exact matrix completion via convex optimization Hit paper breakdown → | 2012 | 560 |
| 9 | Tensor completion and low-n-rank tensor recovery via convex optimization Hit paper breakdown → | 2011 | 510 |
| 10 | Atomic Norm Denoising With Applications to Line Spectral Estimation Hit paper breakdown → | 2013 | 367 |
| 11 | A Tour of Reinforcement Learning: The View from Continuous Control Hit paper breakdown → | 2018 | 337 |
| 12 | Occupy the cloud Hit paper breakdown → | 2017 | 285 |
| 13 | Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning | 2008 | 260 |
| 14 | Ernest: efficient performance prediction for large-scale advanced analytics Hit paper breakdown → | 2016 | 230 |
| 15 | K-Planes: Explicit Radiance Fields in Space, Time, and Appearance Hit paper breakdown → | 2023 | 224 |
| 16 | 2014 | 221 | |
| 17 | On the Sample Complexity of the Linear Quadratic Regulator Hit paper breakdown → | 2019 | 190 |
| 18 | 2013 | 169 | |
| 19 | Gradient Descent Only Converges to Minimizers | 2016 | 147 |
| 20 | Train faster, generalize better: stability of stochastic gradient descent | 2016 | 125 |
About Benjamin Recht
Benjamin Recht is a scholar working on Computational Mechanics, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 101 papers that have together received 16.5k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (39 papers), Blind Source Separation Techniques (12 papers), Stochastic Gradient Optimization Techniques (9 papers), Microwave Imaging and Scattering Analysis (9 papers), Control Systems and Identification (8 papers), Machine Learning and Algorithms (8 papers), Advanced Bandit Algorithms Research (6 papers) and Image and Signal Denoising Methods (6 papers). The work is most often cited by research in Computational Mathematics (996 citations), Computational Mechanics (6.8k citations), Computer Vision and Pattern Recognition (5.0k citations), Signal Processing (2.6k citations) and Computer Graphics and Computer-Aided Design (608 citations). Benjamin Recht has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Emmanuel J. Candès, Ali Rahimi, Pablo A. Parrilo, Maryam Fazel, Badri Narayan Bhaskar, Gongguo Tang, Moritz Hardt, Christopher Ré, Samy Bengio and Oriol Vinyals. Their work appears in journals such as IEEE Transactions on Information Theory, Mathematical Programming, Foundations of Computational Mathematics, Communications of the ACM and PLoS ONE.
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.