Demo Data from EDBT 2026 / reviewers in the wild / expert
M. J. Seo
dblp:78/3030
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1994
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory 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.
| Theoretical computer science
1 paper |
Coding theory · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › error-correcting codes
decoding |
0.0 | 1 | 1994 | An efficient soft-decision Reed-Solomon decoding algorithm · IEEE Trans. Inf. Theory 1994 |
Coding theory › error-correcting codes › decoding
errors-and-erasures decoding |
0.0 | 1 | 1994 | An efficient soft-decision Reed-Solomon decoding algorithm · IEEE Trans. Inf. Theory 1994 |
Coding theory › error-correcting codes
reed-solomon codes |
0.0 | 1 | 1994 | An efficient soft-decision Reed-Solomon decoding algorithm · IEEE Trans. Inf. Theory 1994 |
Coding theory › error-correcting codes › decoding
soft-decision decoding |
0.0 | 1 | 1994 | An efficient soft-decision Reed-Solomon decoding algorithm · IEEE Trans. Inf. Theory 1994 |
Coding theory › error-correcting codes › decoding › decoding algorithms › reliability-based decoding
generalized minimum distance decoding |
0.0 | 1 | 1994 | An efficient soft-decision Reed-Solomon decoding algorithm · IEEE Trans. Inf. Theory 1994 |
Methods — techniques the papers use, named apart from their topics
locator polynomials · 0.0iterative erasure reduction · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | An efficient soft-decision Reed-Solomon decoding algorithmabstractWe develop a computationally efficient soft-decision Reed-Solomon (RS) decoding algorithm. Our new algorithm has direct applications to soft-decision decoding procedures such as the generalized-minimum-distance decoding algorithm. Our particular soft-decision decoding technique is not the innovation of the algorithm. The innovation is a new errors-and-erasures RS decoding algorithm that only works with different sets of erasures where the size of each set of erasures is reduced by one for each iteration (i.e., generalized-minimum-distance decoding). A result of each iteration is an error-and-erasure locator polynomial (or locator polynomials) that any RS decoder would produce. Since the new soft-decision RS decoding algorithm makes no assumptions on the d-1 erasures, the algorithm is useful for soft-decision decoding techniques such as generalized-minimum-distance decoding.> Dana J. Taipale, M. J. Seo |
IEEE Trans. Inf. Theory | 2 |