Demo Data from EDBT 2026 / reviewers in the wild / expert
Richard E. Schwartz
dblp:134/4398
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1969
—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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information theory › hypothesis testing › robust detection
constant false alarm rate detection |
0.0 | 1 | 1969 | Minimax CFAR detection in additive Gaussian noise of unknown covariance (Corresp.) · IEEE Trans. Inf. Theory 1969 |
Information theory › hypothesis testing
signal detection |
0.0 | 1 | 1969 | Minimax CFAR detection in additive Gaussian noise of unknown covariance (Corresp.) · IEEE Trans. Inf. Theory 1969 |
Information theory › hypothesis testing › composite hypothesis testing
minimax detection |
0.0 | 1 | 1969 | Minimax CFAR detection in additive Gaussian noise of unknown covariance (Corresp.) · IEEE Trans. Inf. Theory 1969 |
Methods — techniques the papers use, named apart from their topics
invariance theory · 0.0hunt-stein theorem · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1969 | Minimax CFAR detection in additive Gaussian noise of unknown covariance (Corresp.)abstractBy employing invariance theory and the Hunt-Stein theorem in particular, CFAR and minimax detectors are derived for a signal of unknown phase in the presence of additive Gaussian noise of unknown covariance. Richard E. Schwartz |
IEEE Trans. Inf. Theory | 1 |