Demo Data from EDBT 2026 / reviewers in the wild / expert
R. F. Dressler
dblp:15/1011
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1964
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 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.
| Artificial intelligence
1 paper |
Learning theory · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Learning theory
statistical pattern recognition |
0.0 | 1 | 1964 | Error Rates for Two Methods of Statistical Pattern Recognition · J. ACM 1964 |
Machine learning › Learning theory
error rate analysis |
0.0 | 1 | 1964 | Error Rates for Two Methods of Statistical Pattern Recognition · J. ACM 1964 |
Methods — techniques the papers use, named apart from their topics
threshold devices · 0.0probability density curves · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1964 | Error Rates for Two Methods of Statistical Pattern RecognitionabstractAbstracl.A mathematical analysis is made for the operation of a threshohl-type statistical pattern recognition system, and explicit expressions of the error rates for statistical independence among the nmsks are derived.Analogous expressions are presented for a more complex mode of operation using probability density curves instead of thresholds.The quantitative advantages of the latter system are exhibited.The effect of internal correlations in both methods is discussed.A third analysis is presented for an improved form of threshold device using optimal threshold positions for every mask; its error rate is compared with the density-curve system.A special case of this general formula is shown to agree, when differently interpreted, witt, a result obtained by Golay for detection of weak communication signals.The formulas also furnish a convenient method for measuring overa|l or effective correlation in a system.A method is suggested to reduce the storage requirements of the more complex method to that of the threshold devices, and a recommendation made to exploit the superior capabilities of the density-curve method. R. F. Dressler, W. Werner |
J. ACM | 1 |