Anselm Blumer

4.1k total citations · 2 hit papers
18 papers, 2.4k citations indexed

About

Anselm Blumer is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Anselm Blumer has authored 18 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computational Theory and Mathematics, 11 papers in Artificial Intelligence and 8 papers in Molecular Biology. Recurrent topics in Anselm Blumer's work include Algorithms and Data Compression (10 papers), semigroups and automata theory (5 papers) and Machine Learning and Algorithms (5 papers). Anselm Blumer is often cited by papers focused on Algorithms and Data Compression (10 papers), semigroups and automata theory (5 papers) and Machine Learning and Algorithms (5 papers). Anselm Blumer collaborates with scholars based in United States. Anselm Blumer's co-authors include Andrzej Ehrenfeucht, David Haussler, Manfred K. Warmuth, Kyongbum Lee, Ross M. McConnell, Joel Seiferas, Robert J. McEliece, Benjamin Hescott, Donna K. Slonim and Andrew Fox and has published in prestigious journals such as Bioinformatics, IEEE Transactions on Information Theory and Journal of the ACM.

In The Last Decade

Anselm Blumer

17 papers receiving 2.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Learnability and the Vapnik-Chervonenkis dimension

1989 1.1k citations Anselm Blumer, Andrzej Ehrenfeucht et al. Journal of the ACM profile →
Occam's Razor

1987 692 citations Anselm Blumer, Andrzej Ehrenfeucht et al. Information Processing Letters profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Anselm Blumer United States	10	1.9k	786	314	240	211	18	2.4k
Moshe Sipper Israel	26	1.5k 0.8×	952 1.2×	758 2.4×	232 1.0×	250 1.2×	143	2.6k
L. Darrell Whitley United States	27	1.9k 1.0×	867 1.1×	160 0.5×	170 0.7×	559 2.6×	71	3.1k
Erick Cantú‐Paz United States	25	2.4k 1.3×	1.0k 1.3×	230 0.7×	233 1.0×	379 1.8×	46	3.6k
Heinz Mühlenbein Germany	25	2.6k 1.4×	1.1k 1.5×	226 0.7×	191 0.8×	332 1.6×	62	3.9k
Terence C. Fogarty United Kingdom	21	1.3k 0.7×	486 0.6×	148 0.5×	99 0.4×	168 0.8×	89	2.0k
Lawrence J. Fogel United States	18	1.6k 0.9×	1.0k 1.3×	609 1.9×	236 1.0×	136 0.6×	47	3.3k
Robert E. Keller United States	8	1.2k 0.6×	236 0.3×	357 1.1×	97 0.4×	97 0.5×	20	1.8k
Hisao Tamaki Japan	16	880 0.5×	472 0.6×	96 0.3×	359 1.5×	307 1.5×	62	1.8k
Brad L. Miller United States	7	786 0.4×	405 0.5×	82 0.3×	109 0.5×	145 0.7×	7	1.5k
Nicol N. Schraudolph Switzerland	22	1.4k 0.7×	424 0.5×	425 1.4×	541 2.3×	125 0.6×	45	2.5k

Countries citing papers authored by Anselm Blumer

Since Specialization

Citations

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

Fields of papers citing papers by Anselm Blumer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anselm Blumer

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

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

Blumer, Anselm, et al.. (2024). Approximate IsoRank for Scalable and Functionally Meaningful Cross-Species Alignments of Protein Interaction Networks. Journal of Computational Biology. 31(10). 990–1007.

Dammann, Olaf, Kenneth Chui, & Anselm Blumer. (2018). A Causally Naïve and Rigid Population Model of Disease Occurrence Given Two Non-Independent Risk Factors. Online Journal of Public Health Informatics. 10(2). e216–e216. 3 indexed citations

Fox, Andrew, Benjamin Hescott, Anselm Blumer, & Donna K. Slonim. (2011). Connectedness of PPI network neighborhoods identifies regulatory hub proteins. Bioinformatics. 27(8). 1135–1142. 23 indexed citations

Blumer, Anselm, et al.. (2006). An algorithm for modularity analysis of directed and weighted biological networks based on edge-betweenness centrality. Bioinformatics. 22(24). 3106–3108. 187 indexed citations

Blumer, Anselm, Andrzej Ehrenfeucht, David Haussler, & Manfred K. Warmuth. (1989). Learnability and the Vapnik-Chervonenkis dimension. Journal of the ACM. 36(4). 929–965. 1058 indexed citations breakdown →

Blumer, Anselm, Andrzej Ehrenfeucht, & David Haussler. (1989). Average sizes of suffix trees and DAWGs. Discrete Applied Mathematics. 24(1-3). 37–45. 28 indexed citations

Blumer, Anselm & Nick Littlestone. (1989). Learning faster than promised by the Vapnik-Chervonenkis dimension. Discrete Applied Mathematics. 24(1-3). 47–53. 5 indexed citations

Blumer, Anselm. (1989). Noiseless compression using non-Markov models. NASA STI Repository (National Aeronautics and Space Administration). 1 indexed citations

Blumer, Anselm & Robert J. McEliece. (1988). The Renyi redundancy of generalized Huffman codes. IEEE Transactions on Information Theory. 34(5). 1242–1249. 20 indexed citations

10.

Blumer, Anselm. (1987). Minimax universal noiseless coding for unifilar and Markov sources (Corresp.). IEEE Transactions on Information Theory. 33(6). 925–930. 4 indexed citations

11.

Blumer, Anselm, Andrzej Ehrenfeucht, David Haussler, & Manfred K. Warmuth. (1987). Occam's Razor. Information Processing Letters. 24(6). 377–380. 692 indexed citations breakdown →

12.

Blumer, Anselm, et al.. (1987). Complete inverted files for efficient text retrieval and analysis. Journal of the ACM. 34(3). 578–595. 105 indexed citations

13.

Blumer, Anselm, Andrzej Ehrenfeucht, David Haussler, & Manfred K. Warmuth. (1986). Classifying Learnable Geometric Concepts with the Vapnik-Chervonenkis Dimension (Extended Abstract). 90. 273–282. 2 indexed citations

14.

Blumer, Anselm, Andrzej Ehrenfeucht, David Haussler, & Manfred K. Warmuth. (1986). Classifying learnable geometric concepts with the Vapnik-Chervonenkis dimension. 273–282. 122 indexed citations

15.

Blumer, Anselm, et al.. (1985). The smallest automation recognizing the subwords of a text. Theoretical Computer Science. 40. 31–55. 156 indexed citations

16.

Blumer, Anselm, et al.. (1984). Building a complete inverted file for a set of text files in linear time. 349–358. 8 indexed citations

17.

Blumer, Anselm, et al.. (1983). Linear size finite automata for the set of all subwords of a word - an outline of results.. Bulletin of the European Association for Theoretical Computer Science. 21. 12–20. 24 indexed citations

18.

Blumer, Anselm. (1982). Bounds on the Redundancy of Noiseless Source Coding. 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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