Demo Data from EDBT 2026 / reviewers in the wild / expert
Rahim Samei
dblp:119/5945
· DBLP profile ↗
4ranked-venue papers
4as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 3 first-authorTheory 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 |
Computational complexity · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computational complexity
learning theory |
0.2 | 1 | 2014 | Sample Compression for Multi-label Concept Classes · COLT 2014 |
Computational complexity › learning theory
sample compression |
0.2 | 1 | 2014 | Sample Compression for Multi-label Concept Classes · COLT 2014 |
Computational complexity › learning theory
VC dimension |
0.1 | 1 | 2014 | Sample Compression for Multi-label Concept Classes · COLT 2014 |
Methods — techniques the papers use, named apart from their topics
sample compression schemes · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Generalizing Labeled and Unlabeled Sample Compression to Multi-label Concept Classes
Rahim Samei, Boting Yang, Sandra Zilles |
ALT | 1 |
| 2014 | Sample Compression for Multi-label Concept ClassesabstractThis paper studies labeled sample compression for multi-label concept classes. For a specific extension of the notion of VC-dimension to multi-label classes, we prove that every maximum multi-label class of dimension d has a sample compression scheme in which every sample is compressed to a subset of size at most d. We further show that every multi-label class of dimension 1 has a sample compression scheme using only sets of size at most 1. As opposed to the binary case, the latter result is not immediately implied by the former, since there are multi-label concept classes of dimension 1 that are not contained in maximum classes of dimension 1. Rahim Samei, Pavel Semukhin, Boting Yang, Sandra Zilles |
COLT | 1 |
| 2014 | Algebraic methods proving Sauer's bound for teaching complexity
Rahim Samei, Pavel Semukhin, Boting Yang, Sandra Zilles |
Theor. Comput. Sci. | 1 |
| 2012 | Sauer's Bound for a Notion of Teaching Complexity
Rahim Samei, Pavel Semukhin, Boting Yang, Sandra Zilles |
ALT | 1 |