Publications associées à Capturing the Moment: Lightweight Similarity Computations

Publications associées (32)

Boosting Protein Graph Representations through Static-Dynamic Fusion

Pengkang Guo, Pierre Vandergheynst, Bruno Emanuel Ferreira De Sousa Correia, Daniel Probst

Machine learning for protein modeling faces significant challenges due to proteins' inherently dynamic nature, yet most graph-based machine learning methods rely solely on static structural information. Recently, the growing availability of molecular dynam ...

2025

Incentive Mechanism in the Sponsored Content Market With Network Effects

Olga Fink

We propose an incentive mechanism for the sponsored content provider (CP) market in which the communication of users can be represented by a graph, and the private information of the users is assumed to have a continuous distribution function. The CP stipu ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Network Alignment With Holistic Embeddings

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong, Thanh Trung Huynh

Network alignment is the task of identifying topologically and semantically similar nodes across (two) different networks. It plays an important role in various applications ranging from social network analysis to bioinformatic network interactions. Howeve ...

IEEE COMPUTER SOC2023

Privacy-Preserving Machine Learning on Graphs

Sina Sajadmanesh

Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

EPFL2023

Preliminary metadata paper. Data Domotopia: a web-based survey about home-making in a moving world

Vincent Kaufmann, Luca Giovanni Pattaroni, Guillaume Simon Joseph Drevon, Marc-Edouard Baptiste Grégoire Schultheiss, Garance Clément, Fiona Ines Del Puppo

This questionnaire Data Domotopia is a 100+ multi-purpose items about home-making and stillness in a moving world. The survey covers most of the contemporary issues related to home-making. This includes the domestic space and gender issues; the socio-spati ...

2022

Dynamic Personalized Ranking

Jérémie Rappaz

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

EPFL2022

Explainability and Graph Learning From Social Interactions

Ali H. Sayed, Stefan Vlaski, Valentina Shumovskaia, Konstantinos Ntemos

Social learning algorithms provide models for the formation of opinions over social networks resulting from local reasoning and peer-to-peer exchanges. Interactions occur over an underlying graph topology, which describes the flow of information among the ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Hidden Markov Modeling Over Graphs

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Mert Kayaalp

This work proposes a multi-agent filtering algorithm over graphs for finite-state hidden Markov models (HMMs), which can be used for sequential state estimation or for tracking opinion formation over dynamic social networks. We show that the difference fro ...

IEEE2022

Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

The impact of NFT profile pictures within social network communities

Marco Mattavelli, Simone Casale Brunet

This paper presents an analysis of the role of social media, specifically Twitter, in the context of non-fungible tokens, better known as NFTs. Such emerging technology framing the creation and exchange of digital object, started years ago with early proje ...

ACM2022

Relative, local and global dimension in complex networks

Alexis Arnaudon

Dimension is a fundamental property of objects and the space in which they are embedded. Yet ideal notions of dimension, as in Euclidean spaces, do not always translate to physical spaces, which can be constrained by boundaries and distorted by inhomogenei ...

Nature Portfolio2022

Maintenance scheduling of manufacturing systems based on optimal price of the network

Olga Fink

Goods can exhibit positive externalities impacting decisions of customers in social networks. Suppliers can integrate these externalities in their pricing strategies to increase their revenue. Besides optimizing the prize, suppliers also have to consider t ...

Elsevier2022

Discovering Interaction Patterns in Online Learning Environments : A Learning Analytics Research

Mina Shirvani Boroujeni

The increasing amount of data collected in online learning environments provides unique opportunities to better understand the learning processes in different educational settings. Learning analytics research aims at understanding and optimizing learning a ...

EPFL2018

Smart Toys plus plus : Exploiting the Social Connectedness for Playing and Learning

Ayberk Özgür, Arzu Güneysu Özgür

Under the umbrella of smart toys, a myriad of interactive systems have addressed a variety of scenarios considering entertainment, education, sustainability, social and environmental learning through play. Tangibles and small toy robots prevail; but intera ...

ASSOC COMPUTING MACHINERY2021

True scale-free networks hidden by finite size effects

Andrea Rinaldo, Amos Maritan, Samir Suweis

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statisti ...

National Academy of Sciences2021

Collaborative Filtering Under a Sybil Attack: Similarity Metrics do Matter!

Rachid Guerraoui, Anne-Marie Kermarrec, Antoine Rault

Recommendation systems help users identify interesting content, but they also open new privacy threats. In this paper, we deeply analyze the effect of a Sybil attack that tries to infer information on users from a user-based collaborative-filtering recomme ...

IEEE2018

Designing Gamified Activities with Haptic-Enabled Tangible Robots for Therapy and Assistance

Arzu Güneysu Özgür

In this thesis, we contribute to the field of rehabilitation robotics by designing haptic-enabled tangible robot-based activities and exploring their added value for therapy and assistance. The research specifically focuses on the design and development of ...

EPFL2021

Automatic Online Fake News Detection Combining Content and Social Signals

Stefano Moret

The proliferation and rapid diffusion of fake news on the Internet highlight the need of automatic hoax detection systems. In the context of social networks, machine learning (ML) methods can be used for this purpose. Fake news detection strategies are tra ...

IEEE2018

Privacy in Recommender Systems

Mahsa Taziki

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. Recommenders are machine learning approach and are becoming one of the main ways to navigate the Internet. They recommend appropria ...

EPFL2018

A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins

Jean-Pierre Hubaux, Kévin Clément Huguenin, Igor Bilogrevic, Reza Shokri, Italo Ivan Dacosta Petrocelli, Joana Catarina Soares Machado

Location check-ins contain both geographical and semantic information about the visited venues. Semantic information is usually represented by means of tags (e.g., “restaurant”). Such data can reveal some personal information about users beyond what they a ...

2018