Publications related to Diffusion Adaptation Over Networks Under Imperfect Information Exchange and Non-Stationary Data

Altruism, reciprocity, and tokens to reward forwarding data: Is that fair?

Verónica del Carmen Estrada Galiñanes, Arman Babaei

Decentralized storage networks offer services with intriguing possibilities to reduce inequalities in an extremely centralized market. Fair distribution of rewards, however, is still a persistent problem in the current generation of decentralized applicati ...

2024

Notes on Los Angeles

Alfredo Thiermann

Jean-Louis Cohen was a historian and curator of architecture who inspired and impacted the work of many. His unexpected passing this summer was a loss to the entire expanded field of architecture. A pioneer of transnational and transmedial histories of arc ...

2023

The kinectome: A comprehensive kinematic map of human motion in health and disease

Enrico Amico, Antonella Romano, Emahnuel Troisi Lopez

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body ...

WILEY2022

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Nikolaos Geroliminis, Emmanouil Barmpounakis, Jasso Espadaler Clapés

Signalized intersections are a fundamental part of urban networks. Their understanding is crucial to identify congestion patterns, queues, delays, and safety issues in local and network level. In this work, we analyze multimodal vehicle trajectories and pr ...

2022

Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"

Vassily Hatzimanikatis, Homa Mohammadi Peyhani, Anastasia Sveshnikova

Supplementary datasets accompanying the manuscript "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds" published in the Metabolic Engineering Journal (https://doi.org/10.1016/j.ymben.2022.03.013). In line w ...

EPFL Infoscience2022

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Colin Neil Jones, Ye Pu, Andrea Alessandretti, Francisco Fernandes Castro Rego

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Social Learning Under Inferential Attacks

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

A common assumption in the social learning literature is that agents exchange information in an unselfish manner. In this work, we consider the scenario where a subset of agents aims at driving the network beliefs to the wrong hypothesis. The adversaries a ...

IEEE2021

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Wulfram Gerstner, Clément Hongler, Johanni Michael Brea, Francesco Spadaro, Berfin Simsek, Arthur Jacot

We study how permutation symmetries in overparameterized multi-layer neural networks generate `symmetry-induced' critical points. Assuming a network with

L

layers of minimal widths

r_1^*, \ldots, r_{L-1}^*

reaches a zero-loss minimum at $ r_1^*! \c ...

2021

Local Vulnerabilities and Global Robustness of Coupled Dynamical Systems on Complex Networks

Melvyn Sandy Tyloo

Coupled dynamical systems are omnipresent in everyday life. In general, interactions between individual elements composing the system are captured by complex networks. The latter greatly impact the way coupled systems are functioning and evolving in time. ...

EPFL2020

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We present an efficient and accurate people detection approach based on deep learning to detect people attacks and intrusion in video surveillance scenarios Unlike other approaches using background segmentation and pre-processing techniques, which are not ...

2020

Diffusion Adaptation Over Networks Under Imperfect Information Exchange and Non-Stationary Data

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Altruism, reciprocity, and tokens to reward forwarding data: Is that fair?

Notes on Los Angeles

The kinectome: A comprehensive kinematic map of human motion in health and disease

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Social Learning Under Inferential Attacks

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Local Vulnerabilities and Global Robustness of Coupled Dynamical Systems on Complex Networks

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion

Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances

Local Vulnerabilities and Global Robustness of Coupled Dynamical Systems on Complex Networks

Notes on Los Angeles

Altruism, reciprocity, and tokens to reward forwarding data: Is that fair?

Supplementary datasets for "ARBRE: Computational resource to predict pathways towards industrially important aromatic compounds"

Social Learning Under Inferential Attacks

An automatized signal timing detection at signalized intersections with detailed vehicle trajectory data

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

The kinectome: A comprehensive kinematic map of human motion in health and disease

WatchNet plus plus : efficient and accurate depth-based network for detecting people attacks and intrusion