Demo Data from EDBT 2026 / reviewers in the wild / expert
Christian Kuhlmann 0001
dblp:25/4804-1
· DBLP profile ↗
4ranked-venue papers
2as first author
0since 2021 · last 2000
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-authorTheory of computation · 2 · 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.
| Artificial intelligence
2 papers |
Learning theory · 70% Deep learning architectures and training · 30% | |
| Network and information security
1 paper |
Cryptographic protocols and secure computation · 87% Cryptographic primitives and cryptanalysis · 13% | |
| Theoretical computer science
1 paper |
Computational complexity · 100% |
Topics — the 7 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Deep learning architectures and training › feedforward neural network
two-layer neural network |
0.0 | 1 | 2000 | Hardness Results for General Two-Layer Neural Networks · COLT 2000 |
Cryptographic protocols and secure computation
secret sharing |
0.0 | 1 | 2000 | Construction of visual secret sharing schemes with almost optimal contrast · SODA 2000 |
Cryptographic protocols and secure computation › secret sharing
visual cryptography |
0.0 | 1 | 2000 | Construction of visual secret sharing schemes with almost optimal contrast · SODA 2000 |
Machine learning › Learning theory › computational learning theory
exact learning |
0.0 | 1 | 1998 | Structural Results about Exact Learning with Unspecified Attribute Values · COLT 1998 |
Machine learning › Learning theory › query learning
membership and equivalence queries |
0.0 | 1 | 1998 | Structural Results about Exact Learning with Unspecified Attribute Values · COLT 1998 |
Machine learning › Learning theory
query learning |
0.0 | 1 | 1998 | Structural Results about Exact Learning with Unspecified Attribute Values · COLT 1998 |
Cryptographic primitives and cryptanalysis
information-theoretic security |
0.0 | 1 | 2000 | Construction of visual secret sharing schemes with almost optimal contrast · SODA 2000 |
Methods — techniques the papers use, named apart from their topics
combinatorial construction · 0.0VC dimension lower bounds · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2000 | Hardness Results for General Two-Layer Neural Networks
Christian Kuhlmann 0001 |
COLT | 1 |
| 2000 | Construction of visual secret sharing schemes with almost optimal contrast
Christian Kuhlmann 0001, Hans Simon 0001 |
SODA | 1 |
| 2000 | Structural Results about Exact Learning with Unspecified Attribute Values
Andreas Birkendorf, Norbert Klasner, Christian Kuhlmann 0001, Hans Simon 0001 |
J. Comput. Syst. Sci. | 3 |
| 1998 | Structural Results about Exact Learning with Unspecified Attribute ValuesabstractThis paper deals with the UAV learning model of Goldman, Kwek and Scott [7]. ("UAV" is the acronym for "Unspecified Attribute Values".) As in [7], we consider exact learning within the UAV framework, where the learner has to exactly identify an unknown target concept by means of UAV membership (UAV-MQs) and/or UAV equivalence queries (UAV-EQs or UAV-ARB-EQs, respectively). A smooth transition between exact learning in the UAV setting and standard exact learning is obtained by putting a fixed bound r on the number of unspecified attribute values per instance. For r = 0, we obtain the standard model. For r = n (the total number of attributes), we obtain the (unrestricted) UAV model. Between these extremes, we find the hierarchies (UAV-MQ r ) 0rn , (UAV-EQ r ) 0rn , and (UAV-ARB-EQ r ) 0rn . Our main results are as follows. We present lower bounds on the number of ARB-EQs and UAV-MQs in terms of the Vapnik Chervonenkis dimension of the concept class. We show furthermore that a... Andreas Birkendorf, Norbert Klasner, Christian Kuhlmann 0001, Hans Simon 0001 |
COLT | 3 |