Abstract
Using majorization theory via “Robin Hood” elementary operations, optimal lower and upper bounds are derived on Rényi and guessing entropies with respect to either error probability (yielding reverse-Fano and Fano inequalities) or total variation distance to the uniform (yielding reverse-Pinsker and Pinsker inequalities). This gives a general picture of how the notion of randomness can be measured in many areas of computer science.
| Original language | English |
|---|---|
| Article number | 978 |
| Journal | Entropy |
| Volume | 25 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 1 Jul 2023 |
Keywords
- Fano inequality
- Pinsker inequality
- Rényi entropy
- Schur concavity
- data processing inequality
- entropy
- error probability
- guessing entropy
- guessing moments
- majorization
- total variation distance