Andrew Guillory

541 total citations
11 papers, 295 citations indexed

About

Andrew Guillory is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Andrew Guillory has authored 11 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 3 papers in Computer Networks and Communications. Recurrent topics in Andrew Guillory's work include Machine Learning and Algorithms (6 papers), Complexity and Algorithms in Graphs (4 papers) and Optimization and Search Problems (2 papers). Andrew Guillory is often cited by papers focused on Machine Learning and Algorithms (6 papers), Complexity and Algorithms in Graphs (4 papers) and Optimization and Search Problems (2 papers). Andrew Guillory collaborates with scholars based in United States and United Kingdom. Andrew Guillory's co-authors include Jeff Bilmes, Dan Morris, T. Scott Saponas, Ajit Singh, Charles L. Isbell, Tucker Balch, Adam S. Feldman, Frank Dellaert, Andrew N. Stein and Stephen C. Pratt and has published in prestigious journals such as Proceedings of the IEEE, arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Andrew Guillory

10 papers receiving 283 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Andrew Guillory United States 8 127 99 59 44 42 11 295
Alberto Alvarez-Alvarez Spain 11 143 1.1× 98 1.0× 31 0.5× 70 1.6× 43 1.0× 13 302
Reza Hassanpour Türkiye 10 108 0.9× 102 1.0× 55 0.9× 15 0.3× 9 0.2× 34 335
Stasinos Konstantopoulos Greece 8 135 1.1× 79 0.8× 40 0.7× 11 0.3× 14 0.3× 52 263
Zaid Bassfar Saudi Arabia 9 70 0.6× 118 1.2× 38 0.6× 15 0.3× 24 0.6× 33 265
Yi-Ting Chiang Taiwan 10 79 0.6× 142 1.4× 64 1.1× 9 0.2× 21 0.5× 16 249
Юрий Крак Ukraine 10 105 0.8× 57 0.6× 23 0.4× 27 0.6× 10 0.2× 88 335
Raymond Lo Canada 9 148 1.2× 69 0.7× 110 1.9× 13 0.3× 54 1.3× 20 388
S. Amirhassan Monadjemi Iran 13 83 0.7× 172 1.7× 12 0.2× 25 0.6× 9 0.2× 42 422
Mohammad Reza Kangavari Iran 11 209 1.6× 41 0.4× 73 1.2× 11 0.3× 13 0.3× 38 341
Abdiansah Abdiansah Indonesia 6 137 1.1× 40 0.4× 36 0.6× 21 0.5× 11 0.3× 36 289

Countries citing papers authored by Andrew Guillory

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Guillory

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Guillory

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

All Works

11 of 11 papers shown
1.
Morris, Dan, et al.. (2014). RecoFit. 3225–3234. 136 indexed citations
2.
Singh, Ajit, Andrew Guillory, & Jeff Bilmes. (2012). On Bisubmodular Maximization. International Conference on Artificial Intelligence and Statistics. 1055–1063. 19 indexed citations
3.
Guillory, Andrew & Jeff Bilmes. (2012). Active Semi-Supervised Learning using Submodular Functions. arXiv (Cornell University). 274–282. 18 indexed citations
4.
Guillory, Andrew & Jeff Bilmes. (2011). Online Submodular Set Cover, Ranking, and Repeated Active Learning. Neural Information Processing Systems. 24. 1107–1115. 9 indexed citations
5.
Guillory, Andrew & Jeff Bilmes. (2011). Simultaneous Learning and Covering with Adversarial Noise. International Conference on Machine Learning. 369–376. 22 indexed citations
6.
Guillory, Andrew & Jeff Bilmes. (2010). Interactive Submodular Set Cover. arXiv (Cornell University). 415–422. 22 indexed citations
7.
Guillory, Andrew, Sumit Basu, & Dan Morris. (2010). User-Specific Learning for Recognizing a Singer's Intended Pitch. Proceedings of the AAAI Conference on Artificial Intelligence. 24(1). 960–966.
8.
Guillory, Andrew & Jeff Bilmes. (2009). Label Selection on Graphs. Neural Information Processing Systems. 22. 691–699. 23 indexed citations
9.
Guillory, Andrew, Erick Chastain, & Jeff Bilmes. (2009). Active Learning as Non-Convex Optimization. International Conference on Artificial Intelligence and Statistics. 201–208. 7 indexed citations
10.
Balch, Tucker, Frank Dellaert, Adam S. Feldman, et al.. (2006). How Multirobot Systems Research will Accelerate our Understanding of Social Animal Behavior. Proceedings of the IEEE. 94(7). 1445–1463. 36 indexed citations
11.
Guillory, Andrew, Hai Nguyen, Tucker Balch, & Charles L. Isbell. (2006). Learning executable agent behaviors from observation. 795–797. 3 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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