Michael W. Mahoney

24.7k citations
166 papers · 11.3k indexed · 8 hit papers · h-index 44
Topics
Sparse and Compressive Sensing Techniques (46 papers)Stochastic Gradient Optimization Techniques (42 papers)Face and Expression Recognition (14 papers)

In The Last Decade

Michael W. Mahoney

157 papers receiving 10.7k citations

Hit Papers

A five-site model for liquid water and the reproduction o...20002026200820172000200920102008200950010001.5k

Peers

Michael W. Mahoney
Comparison fields: 5 of 203
  • Artificial Intelligence 4.1k
  • Statistical and Nonlinear Physics 2.3k
  • Computer Vision and Pattern Recognition 2.3k
  • Computational Mechanics 2.0k
  • Atomic and Molecular Physics, and Optics 1.2k
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Countries citing papers authored by Michael W. Mahoney

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Michael W. Mahoney

This figure shows the co-authorship network connecting the top 25 collaborators of Michael W. Mahoney. A scholar is included among the top collaborators of Michael W. Mahoney 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 W. Mahoney. Michael W. Mahoney is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2
AI and Memory Wallbreakdown →
79
3 7
4 0
5 2
6
HAWQ-V3: Dyadic Neural Network Quantization
30
7
Lipschitz Recurrent Neural Networks
3
8
ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
3
9
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism.
4
10
Distributed Second-order Convex Optimization
1
11
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
8
12
The Union of Intersections (UoI) method for interpretable data driven discovery and prediction
1
13
Spectral Gap Error Bounds for Improving CUR Matrix Decomposition and the Nystrom Method
4
14 31
15 45
16
Semi-supervised Eigenvectors for Locally-biased Learning
2
17
On the Hyperbolicity of Small-World Networks and Tree-Like Graphs
1
18 111
19
Unsupervised Feature Selection for the k-means Clustering Problem
80
20 158

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) and Face and Expression Recognition (14 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.

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