Publications related to Pliable Index Coding

A Functional Perspective on Information Measures

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

EPFL2022

A Comparison of optimal measurement-system design with engineering judgement for bridge load testing

Ian Smith, Numa Joy Bertola

Due to conservative approaches in construction design and practice, infrastructure often has hidden reserve capacity. When quantified, this reserve has potential to improve decisions related to asset management. Field measurements, collected through load t ...

2021

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Erixhen Sula

Network information theory studies the communication of information in a network and considers its fundamental limits. Motivating from the extensive presence of the networks in the daily life, the thesis studies the fundamental limits of particular network ...

EPFL2021

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations

Michael Christoph Gastpar, Sung Hoon Lim, Adriano Pastore, Chen Feng

Algebraic network information theory is an emerging facet of network information theory, studying the achievable rates of random code ensembles that have algebraic structure, such as random linear codes. A distinguishing feature is that linear combinations ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Framework to Approximate the Value of Information of Bridge Load Testing for Reserve Capacity Assessment

Ian Smith, Numa Joy Bertola, Marco Proverbio

In developed countries, structural assessment of existing bridges should not be performed using the same conservative models that are used at the design stage. Field measurements of real behavior provide additional information for the inference of previous ...

2020

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Kerstin Preuschoff, Leyla Loued-Khenissi

Uncertainty presents a problem for both human and machine decision-making. While utility maximization has traditionally been viewed as the motive force behind choice behavior, it has been theorized that uncertainty minimization may supersede reward motivat ...

2020

Converse for Multi-Server Single-Message PIR with Side Information

Michael Christoph Gastpar, Su Li

Multi-server single-message private information retrieval is studied in the presence of side information. In this problem, K independent messages are replicatively stored at N non-colluding servers. The user wants to privately download one message from the ...

2020

Robust Generalization via $\alpha$-Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi

\alpha

-Divergences and Sibson’s

\alpha

-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence and Shannon’s Mutual ...

ETHZ2020

Subadditivity Beyond Trees and the Chi-Squared Mutual Information

Emmanuel Abbé, Enric Boix Adsera

Evans et al. [1] proved the subadditivity of the mutual information in the broadcasting on tree model with binary vertex labels and symmetric edge channels. They raised the question of whether such subadditivity extends to loopy graphs in some appropriate ...

IEEE2019

Learning and Adaptive Data Analysis via Maximal Leakage

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

There has been growing interest in studying connections between generalization error of learning algorithms and information measures. In this work, we generalize a result that employs the maximal leakage, a measure of leakage of information, and explore ho ...

IEEE2019

Pliable Index Coding

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A Functional Perspective on Information Measures

A Comparison of optimal measurement-system design with engineering judgement for bridge load testing

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations

Framework to Approximate the Value of Information of Bridge Load Testing for Reserve Capacity Assessment

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Converse for Multi-Server Single-Message PIR with Side Information

Robust Generalization via $\alpha$-Mutual Information

Subadditivity Beyond Trees and the Chi-Squared Mutual Information

Learning and Adaptive Data Analysis via Maximal Leakage

A Functional Perspective on Information Measures

Framework to Approximate the Value of Information of Bridge Load Testing for Reserve Capacity Assessment

A Comparison of optimal measurement-system design with engineering judgement for bridge load testing

Converse for Multi-Server Single-Message PIR with Side Information

Feedback and Common Information: Bounds and Capacity for Gaussian Networks

Information Theoretic Characterization of Uncertainty Distinguishes Surprise From Accuracy Signals in the Brain

Subadditivity Beyond Trees and the Chi-Squared Mutual Information

Robust Generalization via $\alpha$-Mutual Information

Learning and Adaptive Data Analysis via Maximal Leakage

Compute-Forward for DMCs: Simultaneous Decoding of Multiple Combinations