Estimating the Topology of Preferential Attachment Graphs Under Partial Observability

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Publications associées (28)

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

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In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

IEEE2023

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

EPFL2023

Short-term dynamics of drainage density based on a combination of channel flow state surveys and water level measurements

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Headwater streams often experience intermittent flow. Consequently, the flowing drainage network expands and contracts and the flowing drainage density (DD) varies over time. Monitoring the DD dynamics is essential to understand the processes controlling i ...

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Last-mile delivery in the logistics chain contributes to congestion in urban networks due to frequent stops. Crowd-shipping is a sustainable and low-cost alternative to traditional delivery but relies heavily on the availability of occasional couriers. In ...

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A model for the consolidation of hybrid textiles considering air entrapment, dissolution and diffusion

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A new model is proposed for the consolidation of hybrid textiles, in which air entrapment and dissolution are considered. One of the key parameters is tow permeability, which is described by the analytical model of Gebart and validated at very high fibre v ...

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Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables

We propose ordering-based approaches for learning the maximal ancestral graph (MAG) of a structural equation model (SEM) up to its Markov equivalence class (MEC) in the presence of unobserved variables. Existing ordering-based methods in the literature rec ...

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Caching and Neutrality

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We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

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On the fast assemblage of finite element matrices with application to nonlinear heat transfer problems

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The finite element method is a well-established method for the numerical solution of partial differential equations (PDEs), both linear and nonlinear. However, the repeated re -assemblage of finite element matrices for nonlinear PDEs is frequently pointed ...

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DARE-GRAM : Unsupervised Domain Adaptation Regression by Aligning Inverse Gram Matrices

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Unsupervised Domain Adaptation Regression (DAR) aims to bridge the domain gap between a labeled source dataset and an unlabelled target dataset for regression problems. Recent works mostly focus on learning a deep feature encoder by minimizing the discrepa ...

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Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment

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Artificial Neural Networks (ANN) are habitually trained via the back-propagation (BP) algorithm. This approach has been extremely successful: Current models like GPT-3 have O(10 11 ) parameters, are trained on O(10 11 ) words and produce awe-inspiring resu ...

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Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Danilo Saccani, Melanie Nicole Zeilinger

IEEE2023

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

Elisabetta Cornacchia

EPFL2023

Short-term dynamics of drainage density based on a combination of channel flow state surveys and water level measurements

Andrea Rinaldo, Izabela Bujak-Ozga, Jana Freiin von Freyberg

Wiley2023