Publications related to From error probability to information theoretic signal and image processing

Evading Voltage-Based Intrusion Detection on Automotive CAN

Mathias Josef Payer, Duo Xu, Rohit Bhatia

The controller area network (CAN) is widely adopted in modern automobiles to enable communications among in-vehicle electronic control units (ECUs). Lacking mainstream network security capabilities due to resource constraints, the CAN is susceptible to the ...

INTERNET SOC2021

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Pascal Frossard, Michael Bronstein, Laura Toni, Xiaowen Dong

The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

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

Sparse and Parametric Modeling with Applications to Acoustics and Audio

Helena Peic Tukuljac

Recent advances in signal processing, machine learning and deep learning with sparse intrinsic structure of data have paved the path for solving inverse problems in acoustics and audio. The main task of this thesis was to bridge the gap between the powerfu ...

EPFL2020

Analog signal processing with topological metamaterials

Farzad Zangeneh Nejad

Originally discovered in condensed matter systems, topological insulators (TIs) have been ubiquitously extended to various fields of classical wave physics including photonics, phononics, acoustics, mechanics, and microwaves. In the bulk, like any other in ...

EPFL2020

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

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

Occupancy detection and tracking in buildings using floor-vibration signals

Slah Drira

In sensed buildings, information related to occupant movement helps optimize important functionalities such as security enhancement, energy management, and caregiving. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. The ...

EPFL2020

Point, Plane, Set, Match! Winning the Echo Grand SLAM

Miranda Krekovic

Some of the most important and challenging problems in science are inverse problems. They allow us to understand phenomena that cannot be measured directly. Inverse problems might not always have a unique or stable solution, or might not have any solution ...

EPFL2020

Optimal errors and phase transitions in high-dimensional generalized linear models

Nicolas Macris, Florent Gérard Krzakala, Lenka Zdeborová, Jean François Emmanuel Barbier

Generalized linear models (GLMs) are used in high-dimensional machine learning, statistics, communications, and signal processing. In this paper we analyze GLMs when the data matrix is random, as relevant in problems such as compressed sensing, error-corre ...

PNAS2019

From error probability to information theoretic signal and image processing

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Evading Voltage-Based Intrusion Detection on Automotive CAN

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Robust Generalization via $\alpha$-Mutual Information

Sparse and Parametric Modeling with Applications to Acoustics and Audio

Analog signal processing with topological metamaterials

Robust Generalization via f−Mutual Information

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

Occupancy detection and tracking in buildings using floor-vibration signals

Point, Plane, Set, Match! Winning the Echo Grand SLAM

Optimal errors and phase transitions in high-dimensional generalized linear models

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

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Evading Voltage-Based Intrusion Detection on Automotive CAN

Point, Plane, Set, Match! Winning the Echo Grand SLAM

Analog signal processing with topological metamaterials

Occupancy detection and tracking in buildings using floor-vibration signals

Robust Generalization via $\alpha$-Mutual Information

Sparse and Parametric Modeling with Applications to Acoustics and Audio

Robust Generalization via f−Mutual Information

Optimal errors and phase transitions in high-dimensional generalized linear models