Publications related to Information theory

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

Nicolas Macris, Florent Gérard Krzakala, Jean François Emmanuel Barbier, Mohamad Baker Dia

We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections. A few examples where this problem is relevant are compressed sensing, sparse superposition codes, and code division multiple access. There has been a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Robust Generalization via f−Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

Given two probability measures P and Q and an event E, we provide bounds on P(E) in terms of Q(E) and f-divergences. In particular, the bounds are instantiated when the measures considered are a joint distribution and the corresponding product of marginals ...

IEEE2020

Single-server Multi-message Private Information Retrieval with Side Information: the General Cases

Michael Christoph Gastpar, Su Li

The single-server multi-message private information retrieval with side information problem is studied for general cases. In this problem, K independent messages are stored at a single server. One user initially has M messages as side information and wants ...

IEEE2020

Sum-Rate Capacity for Symmetric Gaussian Multiple Access Channels With Feedback

Michael Christoph Gastpar, Erixhen Sula

The feedback sum-rate capacity is established for the symmetric

J

-user Gaussian multiple-access channel (GMAC). The main contribution is a converse bound that combines the dependence-balance argument of Hekstra and Willems (1989) with a variant of the f ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Existence of a Spectral Gap in the Affleck-Kennedy-Lieb-Tasaki Model on the Hexagonal Lattice

Marius Christopher Lemm

The S=1 Affleck-Kennedy-Lieb-Tasaki (AKLT) quantum spin chain was the first rigorous example of an isotropic spin system in the Haldane phase. The conjecture that the S=3/2 AKLT model on the hexagonal lattice is also in a gapped phase has remained open, de ...

2020

Lane Detection and Lane Changing Phenomena Identification with Data from a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

In the era of big data, new transportation-related concepts and methodologies need to be proposed for understanding how congestion propagates. pNEUMA, a unique dataset that was acquired during a first-of-its-kind experiment with a swarm of drones over a de ...

2020

Exploiting Errors for Efficiency: A Survey from Circuits to Applications

Babak Falsafi, Alexandros Daglis, Eva Darulova, Mattia Cacciotti, Damien Zufferey, Sasa Misailovic

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from cor ...

ASSOC COMPUTING MACHINERY2020

On Maintaining Linear Convergence of Distributed Learning and Optimization Under Limited Communication

Na Li, Hossein Shokri Ghadikolaei

In distributed optimization and machine learning, multiple nodes coordinate to solve large problems. To do this, the nodes need to compress important algorithm information to bits so that it can be communicated over a digital channel. The communication tim ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

On the Universality of Low-Density Parity-Check Block Codes

Rüdiger Urbanke, Wei Liu

An important class of modern channel codes is the capacity-achieving sequences of low-density parity-check block codes. Such sequences are usually designed for the binary erasure channel and are decoded by iterative message-passing algorithms. In this pape ...

IEEE2020

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

We propose an information theoretic framework for quantitative assessment of acoustic models used in hidden Markov model (HMM) based automatic speech recognition (ASR). The HMM backend expects that (i) the acoustic model yields accurate state conditional e ...

ELSEVIER2020

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Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

Robust Generalization via f−Mutual Information

Single-server Multi-message Private Information Retrieval with Side Information: the General Cases

Sum-Rate Capacity for Symmetric Gaussian Multiple Access Channels With Feedback

Existence of a Spectral Gap in the Affleck-Kennedy-Lieb-Tasaki Model on the Hexagonal Lattice

Lane Detection and Lane Changing Phenomena Identification with Data from a Swarm of Drones

Exploiting Errors for Efficiency: A Survey from Circuits to Applications

On Maintaining Linear Convergence of Distributed Learning and Optimization Under Limited Communication

On the Universality of Low-Density Parity-Check Block Codes

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Sum-Rate Capacity for Symmetric Gaussian Multiple Access Channels With Feedback

On the Universality of Low-Density Parity-Check Block Codes

Exploiting Errors for Efficiency: A Survey from Circuits to Applications

On Maintaining Linear Convergence of Distributed Learning and Optimization Under Limited Communication

Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation

Robust Generalization via f−Mutual Information

Single-server Multi-message Private Information Retrieval with Side Information: the General Cases

Lane Detection and Lane Changing Phenomena Identification with Data from a Swarm of Drones

Existence of a Spectral Gap in the Affleck-Kennedy-Lieb-Tasaki Model on the Hexagonal Lattice

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR