EDBT 2026 Demo / reviewers in the wild / expert
V. Rathi
dblp:56/2018
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2006
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 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 · 56% Information theory · 36% Combinatorics and discrete mathematics · 8% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information theory
asymptotic analysis |
0.1 | 1 | 2006 | On the Asymptotic Weight and Stopping Set Distribution of Regular LDPC Ensembles · IEEE Trans. Inf. Theory 2006 |
Coding theory
code ensembles |
0.1 | 1 | 2006 | On the Asymptotic Weight and Stopping Set Distribution of Regular LDPC Ensembles · IEEE Trans. Inf. Theory 2006 |
Coding theory › error-correcting codes
LDPC codes |
0.1 | 1 | 2006 | On the Asymptotic Weight and Stopping Set Distribution of Regular LDPC Ensembles · IEEE Trans. Inf. Theory 2006 |
Information theory › probability theory › measure concentration
concentration inequalities |
0.0 | 1 | 2006 | On the Asymptotic Weight and Stopping Set Distribution of Regular LDPC Ensembles · IEEE Trans. Inf. Theory 2006 |
Combinatorics and discrete mathematics › moment analysis
second moment method |
0.0 | 1 | 2006 | On the Asymptotic Weight and Stopping Set Distribution of Regular LDPC Ensembles · IEEE Trans. Inf. Theory 2006 |
Methods — techniques the papers use, named apart from their topics
variance estimation · 0.1second moment method · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | On the Asymptotic Weight and Stopping Set Distribution of Regular LDPC EnsemblesabstractIn this correspondence, we estimate the variance of weight and stopping set distribution of regular low-density parity-check (LDPC) ensembles. Using this estimate and the second moment method we obtain bounds on the probability that a randomly chosen code from regular LDPC ensemble has its weight distribution and stopping set distribution close to respective ensemble averages. We are able to show that a large fraction of total number of codes have their weight and stopping set distribution close to the average V. Rathi |
IEEE Trans. Inf. Theory | 1 |