Michael W. Mahoney
- Computational Mathematics top 0.1%
- Tensor decomposition and applications 12
- Statistical and Nonlinear Physics top 0.2%
- Complex Network Analysis Techniques 13
- Artificial Intelligence top 0.1%
- Stochastic Gradient Optimization Techniques 42
- Machine Learning and Algorithms 12
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- Face and Expression Recognition 14
- Advanced Neural Network Applications 13
- Computational Mechanics top 0.2%
- Sparse and Compressive Sensing Techniques 46
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- Complexity and Algorithms in Graphs 13
- Co-authors
- Petros DrineasWilliam L. JorgensenJure LeskovecKevin LangAnirban DasguptaRavi KannanZhewei YaoChristos Boutsidis
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Nature Communications (1 paper)The Journal of Chemical Physics (4 papers)
- Partner nations
- United StatesAustraliaChina
In The Last Decade
Michael W. Mahoney
157 papers receiving 10.7k citations
Hit Papers
Peers
Comparison fields: 5 of 203
- Computational Mathematics 575
- Statistical and Nonlinear Physics 2.3k
- Artificial Intelligence 4.1k
- Computer Vision and Pattern Recognition 2.3k
- Computational Mechanics 2.0k
Countries citing papers authored by Michael W. Mahoney
This map shows the geographic impact of Michael W. Mahoney'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 W. Mahoney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael W. Mahoney more than expected).
Fields of papers citing papers by Michael W. Mahoney
This network shows the impact of papers produced by Michael W. Mahoney. 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 W. Mahoney. The network helps show where Michael W. Mahoney may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael W. Mahoney, 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 | 2024 | 1 | |
| 2 | AI and Memory Wallbreakdown → | 2024 | 79 |
| 3 | 2024 | 7 | |
| 4 | 2023 | 0 | |
| 5 | 2023 | 2 | |
| 6 | HAWQ-V3: Dyadic Neural Network Quantization | 2021 | 30 |
| 7 | Lipschitz Recurrent Neural Networks | 2021 | 3 |
| 8 | ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training | 2021 | 3 |
| 9 | Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. | 2020 | 4 |
| 10 | Distributed Second-order Convex Optimization | 2018 | 1 |
| 11 | Hessian-based Analysis of Large Batch Training and Robustness to Adversaries | 2018 | 8 |
| 12 | The Union of Intersections (UoI) method for interpretable data driven discovery and prediction | 2017 | 1 |
| 13 | Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nystrom Method | 2015 | 4 |
| 14 | 2013 | 31 | |
| 15 | 2012 | 45 | |
| 16 | Semi-supervised Eigenvectors for Locally-biased Learning | 2012 | 2 |
| 17 | On the Hyperbolicity of Small-World Networks and Tree-Like Graphs | 2012 | 1 |
| 18 | 2009 | 111 | |
| 19 | Unsupervised Feature Selection for the k-means Clustering Problem | 2009 | 80 |
| 20 | 2009 | 158 |
About Michael W. Mahoney
Michael W. Mahoney is a scholar working on Computational Mathematics, Artificial Intelligence and Computational Mechanics, having authored 166 papers that have together received 11.3k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (46 papers), Stochastic Gradient Optimization Techniques (42 papers), Face and Expression Recognition (14 papers), Complexity and Algorithms in Graphs (13 papers), Advanced Neural Network Applications (13 papers), Complex Network Analysis Techniques (13 papers), Machine Learning and Algorithms (12 papers) and Tensor decomposition and applications (12 papers). The work is most often cited by research in Computational Mathematics (575 citations), Statistical and Nonlinear Physics (2.3k citations) and Artificial Intelligence (4.1k citations). Michael W. Mahoney has collaborated with scholars based in United States, Australia and China. Frequent co-authors include Petros Drineas, William L. Jorgensen, Jure Leskovec, Kevin Lang, Anirban Dasgupta, Ravi Kannan, Zhewei Yao, Christos Boutsidis, Kurt Keutzer and S. Muthukrishnan. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Chemical Physics.
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.