Demo Data from EDBT 2026 / reviewers in the wild / expert
Dietrich Wettschereck
dblp:w/DWettschereck
· DBLP profile ↗
10ranked-venue papers
6as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 8 · 5 first-authorDatabases, data management, data science and information retrieval · 3 · 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
3 papers |
Probabilistic and Bayesian machine learning · 27% Learning theory · 27% Kernel, tree and ensemble methods · 27% | |
| Databases, data mining, and information retrieval
1 paper |
Data mining · 50% Database system architecture and tuning · 50% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data mining
data mining system |
0.0 | 1 | 1996 | Extensibility in Data Mining Systems · KDD 1996 |
Database system architecture and tuning
extensibility |
0.0 | 1 | 1996 | Extensibility in Data Mining Systems · KDD 1996 |
Machine learning › Learning theory
classification |
0.0 | 1 | 1993 | Memory-Based Methods for Regression and Classification · NIPS 1993 |
Machine learning › Kernel, tree and ensemble methods
nearest neighbor methods |
0.0 | 1 | 1993 | Locally Adaptive Nearest Neighbor Algorithms · NIPS 1993 |
Machine learning › Probabilistic and Bayesian machine learning › statistical inference
regression |
0.0 | 1 | 1993 | Memory-Based Methods for Regression and Classification · NIPS 1993 |
Machine learning › Deep learning architectures and training › feedforward neural network
radial basis function network |
0.0 | 1 | 1991 | Improving the Performance of Radial Basis Function Networks by Learning Center Locations · NIPS 1991 |
Methods — techniques the papers use, named apart from their topics
nearest neighbor · 0.0memory-based methods · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Visualization and Evaluation Support of Knowledge Discovery through the Predictive Model Markup Language
Dietrich Wettschereck, Alípio Mário Jorge, Steve Moyle |
KES | 1 |
| 1997 | Case-Based Learning: Beyond Classification of Feature Vectors
David W. Aha, Dietrich Wettschereck |
ECML | 2 |
| 1996 | Relational Instance-Based Learning
Werner Emde, Dietrich Wettschereck |
ICML | 2 |
| 1996 | Extensibility in Data Mining Systems
Stefan Wrobel, Dietrich Wettschereck, Edgar Sommer, Werner Emde |
KDD | 2 |
| 1995 | Weighting Features
Dietrich Wettschereck, David W. Aha |
ICCBR | 1 |
| 1995 | An Experimental Comparison of the Nearest-Neighbor and Nearest-Hyperrectangle Algorithms
Dietrich Wettschereck, Thomas G. Dietterich |
Mach. Learn. | 1 |
| 1994 | A Hybrid Nearest-Neighbor and Nearest-Hyperrectangle Algorithm
Dietrich Wettschereck |
ECML | 1 |
| 1993 | Memory-Based Methods for Regression and Classification
Thomas G. Dietterich, Dietrich Wettschereck, Christopher G. Atkeson, Andrew W. Moore 0001 |
NIPS | 2 |
| 1993 | Locally Adaptive Nearest Neighbor Algorithms
Dietrich Wettschereck, Thomas G. Dietterich |
NIPS | 1 |
| 1991 | Improving the Performance of Radial Basis Function Networks by Learning Center Locations
Dietrich Wettschereck, Thomas G. Dietterich |
NIPS | 1 |