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07/03/2023
Quantum Neural Estimation of Entropies
Entropy measures quantify the amount of information and correlations pre...
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11/21/2022
Limit distribution theory for f-Divergences
f-divergences, which quantify discrepancy between probability distributi...
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10/07/2021
Neural Estimation of Statistical Divergences
Statistical divergences (SDs), which quantify the dissimilarity between ...
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03/11/2021
Non-Asymptotic Performance Guarantees for Neural Estimation of 𝖿-Divergences
Statistical distances (SDs), which quantify the dissimilarity between pr...
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09/28/2020
Communicate to Learn at the Edge
Bringing the success of modern machine learning (ML) techniques to mobil...
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04/09/2020
The Secrecy Capacity of Cost-Constrained Wiretap Channels
In many information-theoretic communication problems, adding an input co...
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04/02/2020
Strong Converse for Testing Against Independence over a Noisy channel
A distributed binary hypothesis testing (HT) problem over a noisy channe...
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08/21/2019
Distributed Hypothesis Testing over a Noisy Channel: Error-exponents Trade-off
A distributed hypothesis testing problem with two parties, one referred ...
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07/08/2018
Distributed Hypothesis Testing Under Privacy Constraints
A distributed binary hypothesis testing problem involving two parties, a...
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02/19/2018
Distributed Hypothesis Testing Over Discrete Memoryless Channels
A distributed binary hypothesis testing problem is studied in which mult...
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02/19/2018
