Demo Data from VLDB 2026 / reviewers in the wild / expert
Matthew Goldstein
dblp:134/8793
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1972
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 1 · 1 first-author
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.
| Theoretical computer science
1 paper |
Information theory · 50% Algorithms and data structures · 50% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Algorithms and data structures
classification |
0.0 | 1 | 1972 | kn -nearest neighbor classification · IEEE Trans. Inf. Theory 1972 |
Algorithms and data structures › classification
nearest neighbor classification |
0.0 | 1 | 1972 | kn -nearest neighbor classification · IEEE Trans. Inf. Theory 1972 |
Information theory › pattern recognition
nonparametric classification |
0.0 | 1 | 1972 | kn -nearest neighbor classification · IEEE Trans. Inf. Theory 1972 |
Information theory › pattern recognition
statistical pattern recognition |
0.0 | 1 | 1972 | kn -nearest neighbor classification · IEEE Trans. Inf. Theory 1972 |
Methods — techniques the papers use, named apart from their topics
asymptotic analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1972 | kn -nearest neighbor classificationabstractThek_nnearest neighbor classification rule is a nonparametric classification procedure that assigns a random vectorZto one of two populations\pi_1, \pi_2. Samples of equal sizenare taken from\pi_1and\pi_2and are ordered separately with respect to their distance fromZ = z. The rule assignsZto\pi_1if the distance of thek_nth sample observation from\pi_1tozis less than the distance of thek_nth sample observation from\pi_2toz; otherwiseZis assigned to\pi_2. This rule is equivalent to the Fix and Hodges, "majority rule" [4] or the nearest neighbor rule of Cover and Hart [3]. This paper studies some asymptotic properties of this rule including an expression for a consistent upper bound on the probability of misclassification. Matthew Goldstein |
IEEE Trans. Inf. Theory | 1 |