Demo Data from EDBT 2026 / reviewers in the wild / expert
George Yuhasz
dblp:14/5960
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2
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 · 67% Algorithms and data structures · 33% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory › error-correcting codes › decoding › algebraic decoding
berlekamp-massey algorithm |
0.2 | 1 | 2013 | On the matrix berlekamp-massey algorithm · ACM Trans. Algorithms 2013 |
Coding theory › sequences
linear recurrence sequences |
0.2 | 1 | 2013 | On the matrix berlekamp-massey algorithm · ACM Trans. Algorithms 2013 |
Methods — techniques the papers use, named apart from their topics
loop invariant · 0.2complexity analysis · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | On the matrix berlekamp-massey algorithmabstractWe analyze the Matrix Berlekamp/Massey algorithm, which generalizes the Berlekamp/Massey algorithm [Massey 1969] for computing linear generators of scalar sequences. The Matrix Berlekamp/Massey algorithm computes a minimal matrix generator of a linearly generated matrix sequence and has been first introduced by Rissanen [1972a], Dickinson et al. [1974], and Coppersmith [1994]. Our version of the algorithm makes no restrictions on the rank and dimensions of the matrix sequence. We also give new proofs of correctness and complexity for the algorithm, which is based on self-contained loop invariants and includes an explicit termination criterion for a given determinantal degree bound of the minimal matrix generator. Erich L. Kaltofen, George Yuhasz |
ACM Trans. Algorithms | 2 |
| 2005 | Generic matrix multiplication and memory management in linBoxabstractWe describe the design and implementation of two components in the LinBox library. The first is an implementation of black box matrix multiplication as a lazy matrix-times-matrix product. The implementation uses template meta-programming to set the intermediate vector type used during application of the matrix product. We also describe an interface mechanism that allows incorporation of external components with native memory management such as garbage collection into LinBox. An implementation of the interface based on SACLIB's field arithmetic procedures is presented. Erich L. Kaltofen, Dmitriy Morozov, George Yuhasz |
ISSAC | 3 |