Demo Data from VLDB 2026 / reviewers in the wild / expert
Anastas A. Farjo
dblp:04/4883
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 1976
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 first-authorTheory of computation · 1
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 |
Optimization for machine learning · 100% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Optimization for machine learning
stochastic approximation |
0.0 | 1 | 1972 | On decision-directed estimation and stochastic approximation (Corresp.) · IEEE Trans. Inf. Theory 1972 |
Mathematical optimization › statistical estimation › multivariate estimation
mean estimation |
0.0 | 1 | 1972 | On decision-directed estimation and stochastic approximation (Corresp.) · IEEE Trans. Inf. Theory 1972 |
Mathematical optimization
statistical estimation |
0.0 | 1 | 1972 | On decision-directed estimation and stochastic approximation (Corresp.) · IEEE Trans. Inf. Theory 1972 |
Methods — techniques the papers use, named apart from their topics
stochastic approximation theory · 0.0convergence analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1976 | Analysis and design of decision-directed learning schemes using stochastic approximation
Anastas A. Farjo, Tzay Y. Young |
Inf. Sci. | 1 |
| 1972 | On decision-directed estimation and stochastic approximation (Corresp.)abstractA decision-directed scheme for estimating the mean is expressed as a stochastic approximation algorithm. The algorithm is shown to converge, but not to the true value, by means of the theory of stochastic approximation. A modification of the algorithm that converges to the true value is presented. Tzay Y. Young, Anastas A. Farjo |
IEEE Trans. Inf. Theory | 2 |