Publications associées à Peer Sharing Behaviour in the eDonkey Network, and Implications for the Design of Server-less File Sharing Systems

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Julian Thomas Blackwell, Tanja Christina Käser Jacober, Paola Mejia Domenzain, Vinitra Swamy, Isadora Alves de Salles

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

2024

Planning urban proximities: An empirical analysis of how residential preferences conflict with the urban morphologies and residential practices

Vincent Kaufmann, Luca Giovanni Pattaroni, Marc-Edouard Baptiste Grégoire Schultheiss

Urban proximity planning is foreseen as a solution to foster a “sustainable” city, including economic viability, environmental soundness and social inclusivity. This paper focuses on the inclusivity aspects by questioning the adoption of urban proximities: ...

2024

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis

Hao Lu, Chao Hu, Olga Fink

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

2024

Promoting synergies for sustainability through peer-to-peer sharing: an analysis of drivers and barriers

Claudia Rebeca Binder Signer, Ralph Hansmann

Peer-to-peer (P2P) sharing may foster sustainability synergistically by saving resources, reducing costs and promoting satisfaction of consumer needs and social connectivity. A survey of Swiss and Swedish consumers (N = 1522) was conducted to analyze drive ...

TAYLOR & FRANCIS INC2023

Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining

Qiang Liu, Feng Yu, Yichen Xu

Unsupervised graph representation learning aims to learn low-dimensional node embeddings without supervision while preserving graph topological structures and node attributive features. Previous Graph Neural Networks (GNN) require a large number of labeled ...

Assoc Computing Machinery2023

Fairness and Explainability in Clustering Problems

Xinrui Jia

In this thesis we present and analyze approximation algorithms for three different clustering problems. The formulations of these problems are motivated by fairness and explainability considerations, two issues that have recently received attention in the ...

EPFL2023

A new step forward in realistic cluster lens mass modelling: analysis of Hubble Frontier Field Cluster Abell S1063 from joint lensing, X-ray, and galaxy kinematics data

Johan Richard, Jean-Paul Richard Kneib, Mathilde Jauzac, Benjamin Yvan Alexandre Clement, Benjamin Emmanuel Nicolas Beauchesne

We present a new method to simultaneously and self-consistently model the mass distribution of galaxy clusters that combines constraints from strong lensing features, X-ray emission, and galaxy kinematics measurements. We are able to successfully decompose ...

Oxford Univ Press2023

Transfer learning application of self-supervised learning in ARPES

Gabriel Aeppli

There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

IOP Publishing Ltd2023

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Mehmet Fatih Sahin

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

Subspace clustering in high-dimensions: Phase transitions & Statistical-to-Computational gap

Florent Gérard Krzakala, Lenka Zdeborová, Bruno Loureiro, Luca Pesce, Bruno Loureiro

A simple model to study subspace clustering is the high-dimensional k -Gaussian mixture model where the cluster means are sparse vectors. Here we provide an exact asymptotic characterization of the statistically optimal reconstruction error in this model i ...

2022

Binary Perceptron: Efficient Algorithms Can Find Solutions in a RareWell-Connected Cluster

Emmanuel Abbé

It was recently shown that almost all solutions in the symmetric binary perceptron are isolated, even at low constraint densities, suggesting that finding typical solutions is hard. In contrast, some algorithms have been shown empirically to succeed in fin ...

ASSOC COMPUTING MACHINERY2022

Fair Incentivization of Bandwidth Sharing in Decentralized Storage Networks

Verónica del Carmen Estrada Galiñanes

Peer-to-peer (p2p) networks are not independent of their peers, and the network efficiency depends on peers contributing resources. Because shared resources are not free, this contribution must be rewarded. Peers across the network may share computation po ...

IEEE COMPUTER SOC2022

Applying the Principal Component Analysis for a deeper understanding of the groundwater system: case study of the Bacchiglione Basin (Veneto, Italy)

Andrea Rinaldo

In hydrogeology, it is often difficult to fully understand the hydraulic factors affecting the recharge of groundwater systems. Particularly, at a regional scale, the groundwater system can have different drivers depending on the considered area, i.e., soi ...

PAGEPRESS PUBL2022

Do the majority of stars form as gravitationally unbound?

Richard Irving Anderson

Context. Some of the youngest stars (age less than or similar to 10 Myr) are clustered, while many others are observed scattered throughout star forming regions or in complete isolation. It has been intensively debated whether such scattered or isolated st ...

2022

Covariance matrices for variance-suppressed simulations

Cheng Zhao

Cosmological N-body simulations provide numerical predictions of the structure of the Universe against which to compare data from ongoing and future surveys, but the growing volume of the Universe mapped by surveys requires correspondingly lower statistica ...

OXFORD UNIV PRESS2022

Systematic analysis of low-affinity transcription factor binding site clusters in vitro and in vivo establishes their functional relevance

Sebastian Maerkl, Ivan Istomin, Evan James Olson, Shiyu Cheng, Amir Shahein, Maria Lopez Malo

Binding to binding site clusters has yet to be characterized in depth, and the functional relevance of low-affinity clusters remains uncertain. We characterized transcription factor binding to low-affinity clusters in vitro and found that transcription fac ...

Nature Portfolio2022

Single-Trace Clustering Power Analysis of the Point-Swapping Procedure in the Three Point Ladder of Cortex-M4 SIKE

Aymeric Genet, Novak Kaluderovic

In this paper, the recommended implementation of the post-quantum key exchange SIKE for Cortex-M4 is attacked through power analysis with a single trace by clustering with the k-means algorithm the power samples of all the invocations of the elliptic curve ...

Springer, Cham2022

Geographic clusters of objectively measured physical activity and the characteristics of their built environment in a Swiss urban area

Stéphane Joost, Cédric Gubelmann, Marco André Vieira Ruas, Idris Guessous

Introduction ...

PUBLIC LIBRARY SCIENCE2022

Systematic analysis of biomolecular binding reactions using microfluidic systems

Amir Shahein

Transcription factor binding to a single binding site on DNA and its functional consequence in a promoter context are beginning to be relatively well understood. However, binding to clusters of sites has yet to be characterized in depth, and the functional ...

EPFL2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: cosmological implications from multitracer BAO analysis with galaxies and voids

Jean-Paul Richard Kneib, Huanyuan Shan, Amélie Tamone, Andrei Variu, Jiaxi Yu, Daniel Felipe Forero Sanchez, Cheng Zhao

We construct cosmic void catalogues with the DIVE void finder upon SDSS BOSS DR12 and eBOSS DR16 galaxy samples with BAO reconstruction, and perform a joint BAO analysis using different types of galaxies and the corresponding voids. The BAO peak is evident ...

OXFORD UNIV PRESS2022