Samson Zhou

572 citations
23 papers · 123 · h-index 6

Impact in

Papers in

Samson Zhou

20 papers receiving 115 citations

Peers

Samson Zhou
Comparison fields: 5 of 31
  • Signal Processing 28
  • Artificial Intelligence 64
  • Computational Mathematics 1
  • Computer Networks and Communications 31
  • Infectious Diseases 24
Replace Junji Shikata with:
Junji Shikata Japan
Benjamin Fuller United States
Kevin Yeo United States
Siwei Sun China
Elliot Meyerson United States
Y. Lee South Korea
S. Bae South Korea
Chang‐An Zhao China
Chae Hoon Lim South Korea
Marek Klonowski Poland
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Citations per field
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Citations per year

Countries citing papers authored by Samson Zhou

Since Specialization
Citations

This map shows the geographic impact of Samson Zhou'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 Samson Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samson Zhou more than expected).

Fields of papers citing papers by Samson Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Samson Zhou. 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 Samson Zhou. The network helps show where Samson Zhou may publish in the future.

Co-authors

The 25 scholars most cited alongside Samson Zhou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Samson Zhou Line = papers co-authored together Samson Zhou links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201833
2 201918
3 202010
4 20168
5 20198
6 20217
7 20185
8 20214
9 20184
10 20204
11
Data-Independent Neural Pruning via Coresets
20203
12 20223
13 20223
14 20233
15 20222
16
"Bring Your Own Greedy"+Max: Near-Optimal 1/2-Approximations for Submodular Knapsack.
20192
17 20182
18 20192
19
On Activation Function Coresets for Network Pruning
20191
20 20211

About Samson Zhou

Samson Zhou is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Molecular Biology and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 123 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (9 papers), Cryptography and Data Security (7 papers), Complexity and Algorithms in Graphs (6 papers), Adversarial Robustness in Machine Learning (5 papers), Optimization and Search Problems (4 papers), Coding theory and cryptography (3 papers), Stochastic Gradient Optimization Techniques (3 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Signal Processing (28 citations), Artificial Intelligence (64 citations), Computational Mathematics (1 citation), Computer Networks and Communications (31 citations) and Infectious Diseases (24 citations). Samson Zhou has collaborated with scholars based in United States, Israel and Hong Kong. Frequent co-authors include Jeremiah Blocki, Elena Grigorescu, Sidharth Jaggi, David P. Woodruff, Vladimir Braverman, Grigory Yaroslavtsev, Slobodan Mitrović, Margarita Osadchy, Petros Drineas and Dan Feldman. Their work appears in journals such as IEEE Transactions on Information Theory, Algorithmica, Journal of Cryptology, IEEE Transactions on Neural Networks and Learning Systems and Lecture notes in computer science.

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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