Tyler Neylon

753 total citations
7 papers, 436 citations indexed

About

Tyler Neylon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Tyler Neylon has authored 7 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Signal Processing. Recurrent topics in Tyler Neylon's work include Sparse and Compressive Sensing Techniques (2 papers), Sentiment Analysis and Opinion Mining (2 papers) and Topic Modeling (2 papers). Tyler Neylon is often cited by papers focused on Sparse and Compressive Sensing Techniques (2 papers), Sentiment Analysis and Opinion Mining (2 papers) and Topic Modeling (2 papers). Tyler Neylon collaborates with scholars based in United States and Israel. Tyler Neylon's co-authors include Ryan McDonald, George A. Reis, Sasha Blair-Goldensohn, Dennis Shasha, Lee-Ad Gottlieb, Xiaojian Zhao and Xin Zhang and has published in prestigious journals such as Algorithmica, Symposium on Discrete Algorithms and Meeting of the Association for Computational Linguistics.

In The Last Decade

Tyler Neylon

7 papers receiving 403 citations

Peers

Tyler Neylon
Tyler Neylon
Citations per year, relative to Tyler Neylon Tyler Neylon (= 1×) peers Kenji Tateishi

Countries citing papers authored by Tyler Neylon

Since Specialization
Citations

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

Fields of papers citing papers by Tyler Neylon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tyler Neylon

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

All Works

7 of 7 papers shown
1.
Gottlieb, Lee-Ad & Tyler Neylon. (2015). Matrix Sparsification and the Sparse Null Space Problem. Algorithmica. 76(2). 426–444. 3 indexed citations
2.
Neylon, Tyler. (2010). A locality-sensitive hash for real vectors. Symposium on Discrete Algorithms. 1179–1189. 2 indexed citations
3.
Neylon, Tyler. (2010). A locality-sensitive hash for real vectors. 1179–1189. 2 indexed citations
4.
Blair-Goldensohn, Sasha, et al.. (2008). Building a Sentiment Summarizer for Local Service Reviews. 234 indexed citations
5.
McDonald, Ryan, et al.. (2007). Structured Models for Fine-to-Coarse Sentiment Analysis. Meeting of the Association for Computational Linguistics. 432–439. 176 indexed citations
6.
Zhao, Xiaojian, Xin Zhang, Tyler Neylon, & Dennis Shasha. (2006). Incremental Methods for Simple Problems in Time Series: Algorithms and Experiments. 16. 3–14. 4 indexed citations
7.
Shasha, Dennis & Tyler Neylon. (2006). Sparse solutions for linear prediction problems. 15 indexed citations

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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