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Found 6 papers, 0 papers with code
Lossless Transformations and Excess Risk Bounds in Statistical Inference
After characterizing lossless transformations, i. e., transformations for which the excess risk is zero for all loss functions, we construct a partitioning test statistic for the hypothesis that a given transformation is lossless and show that for i. i. d.
On the Rényi Cross-Entropy
The R\'{e}nyi cross-entropy measure between two distributions, a generalization of the Shannon cross-entropy, was recently used as a loss function for the improved design of deep learning generative adversarial networks.
An Information Bottleneck Problem with Rényi's Entropy
This paper considers an information bottleneck problem with the objective of obtaining a most informative representation of a hidden feature subject to a R\'enyi entropy complexity constraint.
Information Theory Information Theory
Signaling Games for Log-Concave Distributions: Number of Bins and Properties of Equilibria
For sources with two-sided unbounded support, we prove that, for any finite number of bins, there exists a unique equilibrium.
Quantization
Information Theory
Information Theory
Capacity of Generalized Discrete-Memoryless Push-to-Talk Two-Way Channels
In this report, we generalize Shannon's push-to-talk two-way channel (PTT-TWC) by allowing reliable full-duplex transmission as well as noisy reception in the half-duplex (PTT) mode.
Information Theory Information Theory
Information Extraction Under Privacy Constraints
To this end, the so-called {\em rate-privacy function} is introduced to quantify the maximal amount of information (measured in terms of mutual information) that can be extracted from $Y$ under a privacy constraint between $X$ and the extracted information, where privacy is measured using either mutual information or maximal correlation.
