VLDB 2026 Research / reviewers in the wild / expert
Reuven Y. Rubinstein
dblp:49/7027
· DBLP profile ↗
4ranked-venue papers
1as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Databases, data management, data science and information retrieval · 1 · 1 first-authorTheory of computation · 1
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 |
Optimization for machine learning · 36% Kernel, tree and ensemble methods · 36% Reinforcement learning · 28% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Optimization for machine learning › evolutionary computation
cross-entropy method |
0.1 | 1 | 2005 | The cross entropy method for classification · ICML 2005 |
Machine learning › Kernel, tree and ensemble methods
support vector machine |
0.1 | 1 | 2005 | The cross entropy method for classification · ICML 2005 |
Machine learning › Reinforcement learning
policy search |
0.0 | 1 | 2003 | The Cross Entropy Method for Fast Policy Search · ICML 2003 |
Methods — techniques the papers use, named apart from their topics
cross-entropy method · 0.1linear programming · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Application of the cross-entropy method to clustering and vector quantization
Dirk P. Kroese, Reuven Y. Rubinstein, Thomas Taimre |
J. Glob. Optim. | 2 |
| 2005 | The cross entropy method for classificationabstractWe consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term instead of the L1 or L2 norms. In order to solve the optimization problem we use the cross entropy method to search over the possible sets of support vectors. The algorithm consists of solving a sequence of efficient linear programs. We report experiments where our method produces generalization errors that are similar to support vector machines, while using a considerably smaller number of support vectors. Shie Mannor, Dori Peleg, Reuven Y. Rubinstein |
ICML | 3 |
| 2003 | The Cross Entropy Method for Fast Policy Search
Shie Mannor, Reuven Y. Rubinstein, Yohai Gat |
ICML | 2 |
| 1976 | About one of Tsetlin's problems of the collective behavior of stochastic automata
Reuven Y. Rubinstein, J. Har-El |
Inf. Sci. | 1 |