Demo Data from EDBT 2026 / reviewers in the wild / expert
R. Jyothi
dblp:207/9623
· DBLP profile ↗
4ranked-venue papers
4as first author
3since 2021 · last 2022
0000-0002-8335-6103ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 3 · 3 first-author · 3 since 2021Artificial intelligence and machine learning · 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 |
Wireless sensing and localization · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization
range-based localization |
0.4 | 1 | 2020 | SOLVIT: A Reference-Free Source Localization Technique Using Majorization Minimization · IEEE ACM Trans. Audio Speech Lang. Process. 2020 |
Wireless sensing and localization
source localization |
0.4 | 1 | 2020 | SOLVIT: A Reference-Free Source Localization Technique Using Majorization Minimization · IEEE ACM Trans. Audio Speech Lang. Process. 2020 |
Methods — techniques the papers use, named apart from their topics
majorization-minimization · 0.4fixed point algorithm · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | PIANO: A fast parallel iterative algorithm for multinomial and sparse multinomial logistic regression
R. Jyothi, Prabhu Babu |
Signal Process. | 1 |
| 2022 | TELET: A monotonic algorithm to design large dimensional equiangular tight frames for applications in compressed sensing
R. Jyothi, Prabhu Babu |
Signal Process. | 1 |
| 2021 | DYANOM - Dykstra's projection based atomic norm solver
R. Jyothi, Prabhu Babu, Z. Tian |
Signal Process. | 1 |
| 2020 | SOLVIT: A Reference-Free Source Localization Technique Using Majorization MinimizationabstractWe consider the problem of localizing the source using range, and range-difference measurements. Both the problems are non-convex, and non-smooth, and are challenging to solve. In this article, we develop an iterative algorithm - Source Localization Via an Iterative technique (SOLVIT) to localize the source using all the distinct range-difference measurements, i.e., without choosing a reference sensor. SOLVIT is based on the Majorization Minimization approach - in which a novel upper bound is formulated, and minimized to get a closed-form solution at every iteration. We also solve the source localization problem based on range measurements, and rederive the Standard Fixed Point algorithm using the Majorization Minimization approach. By doing so, we show a less intricate way to prove the convergence of the Standard Fixed Point algorithm. Numerical simulations, and experiments in an anechoic chamber confirm that SOLVIT performs better than existing reference-based, and reference-free methods in terms of source positioning accuracy. R. Jyothi, Prabhu Babu |
IEEE ACM Trans. Audio Speech Lang. Process. | 1 |