Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Johannes Grabmeier

dblp:59/1262 · DBLP profile ↗
← Back
3ranked-venue papers
1as first author
0since 2021 · last 2002
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 2Databases, data management, data science and information retrieval · 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 · 91% Algorithms and data structures · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Coding theory › error-correcting codes
decoding
0.011993
Applying Coding Theory to Sparse Interpolation · SIAM J. Comput. 1993
Coding theory › error-correcting codes
reed-muller codes
0.011993
Applying Coding Theory to Sparse Interpolation · SIAM J. Comput. 1993
Coding theory › error-correcting codes
reed-solomon codes
0.011993
Applying Coding Theory to Sparse Interpolation · SIAM J. Comput. 1993
Algorithms and data structures › symbolic computation
sparse interpolation
0.011993
Applying Coding Theory to Sparse Interpolation · SIAM J. Comput. 1993

Methods — techniques the papers use, named apart from their topics

evaluation point construction · 0.0character sums · 0.0
YearPublicationVenuePosition
2002 Techniques of Cluster Algorithms in Data Mining
Johannes Grabmeier, Andreas Rudolph
Data Min. Knowl. Discov.1
1993 Applying Coding Theory to Sparse Interpolation
abstract
Fast interpolation algorithms are presented for sparse sums of characters on the product monoid $U^n $ with values in a field K in two special cases. In the first case, U is a finite cyclic group of order e, and K is a field that contains a root of unity of order e. Here linear codes over ${\mathbb{Z} / {e\mathbb{Z}}}$ can be used to construct sets of evaluation points that allow efficient interpolation by decoding Reed–Solomon codes. In the second case, K is the binary field $GF(2)$, and U is the multiplicative monoid of $GF(2)$. Here sparse sums of characters coincide with sparse Boolean polynomials and can be interpolated using the smallest set of evaluation points by decoding Reed–Muller codes.
Arne Dür, Johannes Grabmeier
SIAM J. Comput.2
1991 On Zero-Testing and Interpolation of k-Sparse Multivariate Polynomials Over Finite Fields
Michael Clausen, Andreas Dress, Johannes Grabmeier, Marek Karpinski
Theor. Comput. Sci.3