EDBT 2026 Demo / reviewers in the wild / expert
Joshua Feinberg
dblp:47/2995
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0002-2869-0010ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Theory 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.
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% | |
| Artificial intelligence
1 paper |
Robot navigation and mapping · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Image and video processing
pattern matching |
0.1 | 1 | 2012 | A Probabilistic Approach to Pattern Matching in the Continuous Domain · IEEE Trans. Pattern Anal. Mach. Intell. 2012 |
Robotics › Robot navigation and mapping › state estimation › kinematic state estimation
path integration |
0.0 | 1 | 2012 | A Probabilistic Approach to Pattern Matching in the Continuous Domain · IEEE Trans. Pattern Anal. Mach. Intell. 2012 |
Methods — techniques the papers use, named apart from their topics
probabilistic modeling · 0.3path integration · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | A Probabilistic Approach to Pattern Matching in the Continuous DomainabstractThe goal of this paper is to solve the following basic problem: Given discrete noisy samples from a continuous signal, compute the probability distribution of its distance from a fixed template. As opposed to the typical restoration problem, which considers a single optimal signal, the computation of the entire probability distribution necessitates integrating over the entire signal space. To achieve this, we apply path integration techniques. The problem is studied in one and two dimensions, and an accurate solution as well as an efficient approximation scheme are provided. Daniel Keren, Michael Werman, Joshua Feinberg |
IEEE Trans. Pattern Anal. Mach. Intell. | 3 |
| 2003 | Probabilistic analysis of a differential equation for linear programming
Asa Ben-Hur, Joshua Feinberg, Shmuel Fishman, Hava T. Siegelmann |
J. Complex. | 2 |