EDBT 2026 Demo / reviewers in the wild / expert
Yuval Domb
dblp:37/10826
· DBLP profile ↗
3ranked-venue papers
3as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 2 · 2 first-authorApplied, interdisciplinary, general and emerging computing · 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
2 papers |
Coding theory · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Coding theory
lattice codes |
0.5 | 2 | 2016 | The Random Coding Bound Is Tight for the Average Linear Code or Lattice · IEEE Trans. Inf. Theory 2016 Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016 |
Coding theory
channel coding |
0.2 | 1 | 2016 | Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016 |
Coding theory › channel coding
error exponent |
0.2 | 1 | 2016 | Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016 |
Coding theory › channel coding
error probability bounds |
0.2 | 1 | 2016 | Non-Random Coding Error Bounds for Lattices · IEEE Trans. Inf. Theory 2016 |
Coding theory › error-correcting codes › block codes
linear code |
0.2 | 1 | 2016 | The Random Coding Bound Is Tight for the Average Linear Code or Lattice · IEEE Trans. Inf. Theory 2016 |
Coding theory › channel coding › error probability bounds
random coding bound |
0.2 | 1 | 2016 | The Random Coding Bound Is Tight for the Average Linear Code or Lattice · IEEE Trans. Inf. Theory 2016 |
Methods — techniques the papers use, named apart from their topics
random ensemble analysis · 0.2minkowski-hlawka theorem · 0.2expurgation · 0.2distance spectrum · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Non-Random Coding Error Bounds for LatticesabstractAn upper bound on the error probability of specific lattices, based on their distance spectrum, is constructed. The derivation is accomplished using a simple alternative to the Minkowski-Hlawka mean-value theorem of the geometry of numbers. In many ways, the new bound greatly resembles the Shulman-Feder bound for linear codes. Based on the new bound, error-exponent and channel-dispersion expressions are derived for specific lattice sequences (of increasing dimension) over the AWGN channel. Measuring a sequence's gap to capacity, using the new asymptotics, is demonstrated. Additional finite dimension results, encountered along the way, are presented. Yuval Domb, Meir Feder |
IEEE Trans. Inf. Theory | 1 |
| 2016 | The Random Coding Bound Is Tight for the Average Linear Code or LatticeabstractIn 1973, Gallager proved that the random-coding bound is exponentially tight for the random code ensemble at all rates, even below expurgation. This result explained that the random-coding exponent does not achieve the expurgation exponent due to the properties of the random ensemble, irrespective of the utilized bounding technique. It has been conjectured that this same behavior holds true for a random ensemble of linear codes. This conjecture is proved in this paper. In addition, it is shown that this property extends to Poltyrev's random-coding exponent for a random ensemble of lattices. Yuval Domb, Ram Zamir, Meir Feder |
IEEE Trans. Inf. Theory | 1 |
| 2012 | Non-random coding error exponent for latticesabstractAn upper bound on the error probability of specific lattices, based on their distance spectrum, is constructed. The derivation is accomplished using a simple alternative to the Minkowski-Hlawka mean-value theorem of the geometry of numbers. In many ways, the new bound greatly resembles the Shulman-Feder bound for linear codes. Based on the new bound, an error exponent is derived for specific lattice sequences (of increasing dimension) over the AWGN channel. Measuring the sequence's gap to capacity, using the new exponent, is demonstrated. Yuval Domb, Meir Feder |
ISIT | 1 |