VLDB 2026 Research / reviewers in the wild / expert
Andrei Sechelea
dblp:152/6263
· DBLP profile ↗
2ranked-venue papers
2as first author
0since 2021 · last 2016
0000-0002-4703-8925ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-authorGraphics, 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.
| Theoretical computer science
1 paper |
Coding theory · 100% | |
| Computer graphics and multimedia
1 paper |
Image and video coding · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › source coding
predictive coding |
0.2 | 1 | 2016 | On the Rate-Distortion Function for Binary Source Coding With Side Information · IEEE Trans. Commun. 2016 |
Coding theory › source coding
rate-distortion theory |
0.2 | 1 | 2016 | On the Rate-Distortion Function for Binary Source Coding With Side Information · IEEE Trans. Commun. 2016 |
Coding theory › source coding › rate-distortion theory
source coding with side information |
0.2 | 1 | 2016 | On the Rate-Distortion Function for Binary Source Coding With Side Information · IEEE Trans. Commun. 2016 |
Coding theory › source coding › side information
wyner-ziv coding |
0.2 | 1 | 2016 | On the Rate-Distortion Function for Binary Source Coding With Side Information · IEEE Trans. Commun. 2016 |
Image and video coding
video compression |
0.1 | 1 | 2016 | On the Rate-Distortion Function for Binary Source Coding With Side Information · IEEE Trans. Commun. 2016 |
Image and video coding › distributed video coding
wyner-ziv video coding |
0.1 | 1 | 2016 | On the Rate-Distortion Function for Binary Source Coding With Side Information · IEEE Trans. Commun. 2016 |
Methods — techniques the papers use, named apart from their topics
rate-distortion analysis · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | The Rate Loss in Binary Source Coding with Decoder Side InformationabstractSummary form only given. Motivated by the correlation channel modeling problem in practical applications, such as distributed video coding, we study the binary source coding of a uniform source with side information, under asymmetric correlation channel assumptions. First, we consider the case where side information is available to both the encoder and decoder, and give an analytical formula for the rate-distortion bound. Then, we consider the side information to be available only to the decoder and present the derivation of the associated Wyner-Ziv rate-distortion bound. Most importantly, we characterize the evolution of the rate-loss suffered by Wyner-Ziv coding, for all possible binary asymmetric correlation channels. Andrei Sechelea, Adrian Munteanu 0001, Samuel Cheng 0001, Nikos Deligiannis |
DCC | 1 |
| 2016 | On the Rate-Distortion Function for Binary Source Coding With Side InformationabstractWe present an in-depth analysis of the problem of lossy compression of binary sources in the presence of correlated side information, where the correlation is given by a generic binary asymmetric channel and the Hamming distance is the distortion metric. Our analysis is motivated by systematic rate-distortion gains observed when applying asymmetric correlation models in Wyner-Ziv video coding. First, we derive for the first time the rate-distortion function for conventional predictive coding in the binary-asymmetric-correlation-channel scenario. Second, we propose a new bound for the case where the side information is only available at the decoder-Wyner-Ziv coding. We conjecture this bound to be tight. We show that the maximum rate needed to encode as well as the maximum rate-loss of Wyner-Ziv coding relative to predictive coding corresponds to uniform sources and symmetric correlations. Importantly, we show that the upper bound on the rate-loss established by Zamir is not tight and that the maximum value is actually significantly lower. Moreover, we prove that the only binary correlation channel that incurs no rate-loss for Wyner-Ziv coding compared with predictive coding is the Z-channel. Finally, we complement our analysis with new compression performance results obtained with our state-of-the-art Wyner-Ziv video coding system. Andrei Sechelea, Adrian Munteanu 0001, Samuel Cheng 0001, Nikos Deligiannis |
IEEE Trans. Commun. | 1 |