Demo Data from SIGIR 2026 / reviewers in the wild / expert
Alexander Jourjine
dblp:36/234
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 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.
| Computer networks
1 paper |
Physical-layer communications · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Physical-layer communications › signal processing for communications
array signal processing |
0.0 | 1 | 1999 | Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics · NIPS 1999 |
Physical-layer communications › signal processing for communications › array signal processing
direction-of-arrival estimation |
0.0 | 1 | 1999 | Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics · NIPS 1999 |
Physical-layer communications › signal processing for communications › statistical signal processing › estimation theory
second-order statistics estimation |
0.0 | 1 | 1999 | Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics · NIPS 1999 |
Methods — techniques the papers use, named apart from their topics
second-order statistics · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Blind separation of disjoint orthogonal signals: demixing N sources from 2 mixturesabstractWe present a novel method for blind separation of any number of sources using only two mixtures. The method applies when sources are (W-)disjoint orthogonal, that is, when the supports of the (windowed) Fourier transform of any two signals in the mixture are disjoint sets. We show that, for anechoic mixtures of attenuated and delayed sources, the method allows one to estimate the mixing parameters by clustering ratios of the time-frequency representations of the mixtures. The estimates of the mixing parameters are then used to partition the time-frequency representation of one mixture to recover the original sources. The technique is valid even in the case when the number of sources is larger than the number of mixtures. The general results are verified on both speech and wireless signals. Alexander Jourjine, Scott T. Rickard, Özgür Yilmaz |
ICASSP | 1 |
| 1999 | Broadband Direction-Of-Arrival Estimation Based on Second Order Statistics
Justinian P. Rosca, Joseph Ó Ruanaidh, Alexander Jourjine, Scott T. Rickard |
NIPS | 3 |