Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page
Demo Data from VLDB 2026 / reviewers in the wild / expert

Lynn Burroughs

dblp:46/5942 · DBLP profile ↗
← Back
7ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 5Theory of computation · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
3 papers
Learning theory · 74% Knowledge representation and reasoning · 26%
Theoretical computer science
1 paper
Computational complexity · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
concept learning		 0.012003
On the Proper Learning of Axis-Parallel Concepts · J. Mach. Learn. Res. 2003
Machine learning › Learning theory › PAC learning
agnostic learning		 0.012002
Bounds for the Minimum Disagreement Problem with Applications to Learning Theory · COLT 2002
Machine learning › Learning theory
PAC learning		 0.012002
On the Proper Learning of Axis Parallel Concepts · COLT 2002
Machine learning › Learning theory › PAC learning
proper learning		 0.012002
On the Proper Learning of Axis Parallel Concepts · COLT 2002
Machine learning › Learning theory › computational learning theory
concept class learning		 0.012002
On the Proper Learning of Axis Parallel Concepts · COLT 2002
Computational complexity
hardness of approximation		 0.012002
Bounds for the Minimum Disagreement Problem with Applications to Learning Theory · COLT 2002

Methods — techniques the papers use, named apart from their topics

learning-theoretic bounds · 0.1proper learning · 0.0proper learning algorithms · 0.0
YearPublicationVenuePosition
2006 Maximizing agreements and coagnostic learning
Nader H. Bshouty, Lynn Burroughs
 Theor. Comput. Sci.2
2005 Maximizing Agreements with One-Sided Error with Applications to Heuristic Learning
Nader H. Bshouty, Lynn Burroughs
 Mach. Learn.2
2003 On the Proper Learning of Axis-Parallel Concepts
Nader H. Bshouty, Lynn Burroughs
 J. Mach. Learn. Res.2
2002 Maximizing Agreements and CoAgnostic Learning
Nader H. Bshouty, Lynn Burroughs
 ALT2
2002 Bounds for the Minimum Disagreement Problem with Applications to Learning Theory
Nader H. Bshouty, Lynn Burroughs
 COLT2
2002 On the Proper Learning of Axis Parallel Concepts
Nader H. Bshouty, Lynn Burroughs
 COLT2
1998 Massaging a Linear Programming Solution to Give a 2-Approximation for a Generalization of the Vertex Cover Problem
Nader H. Bshouty, Lynn Burroughs
 STACS2