Demo Data from EDBT 2026 / reviewers in the wild / expert
Maciej Bialobrzeski
dblp:300/4133
· DBLP profile ↗
1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Theory of computation · 1 · 1 first-author · 1 since 2021
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 |
Information theory · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information theory › information measures › entropy › generalized entropy
rényi entropy |
0.7 | 1 | 2023 | Rényi Entropy and Variance Comparison for Symmetric Log-Concave Random Variables · IEEE Trans. Inf. Theory 2023 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Rényi Entropy and Variance Comparison for Symmetric Log-Concave Random VariablesabstractWe show that for any$\alpha >0$the Rényi entropy of order$\alpha $is minimized, among all symmetric log-concave random variables with fixed variance, either for a uniform distribution or for a two sided exponential distribution. The first case occurs for$\alpha \in (0,\alpha ^{\ast}]$and the second case for$\alpha \in [\alpha ^{\ast},\infty$), where$\alpha ^{\ast}$satisfies the equation$2 \log \alpha ^{\ast}= (\alpha ^{\ast}-1) \log 6$, that is$\alpha ^{\ast} \approx 1.241$. We deduce that the one-sided exponential distribution minimizes Rényi entropy of order$\alpha \geq 2$among all log-concave random variables with fixed variance. Maciej Bialobrzeski, Piotr Nayar |
IEEE Trans. Inf. Theory | 1 |