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Matthias Grossglauser

Cette personne a quitté l’EPFL

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Publications associées (58)

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A User Study of Perceived Carbon Footprint

Patrick Thiran, Matthias Grossglauser, Lucas Maystre, Victor Kristof, Robin Adrien Zbinden

We propose a statistical model to understand people's perception of their carbon footprint. Driven by the observation that few people think of CO2 impact in absolute terms, we design a system to probe people's perception from simple pairwise comparisons of ...

2019

On the Privacy of Anonymized Networks

Matthias Grossglauser, Pedram Pedarsani

The proliferation of online social networks, and the concomitant accumulation of user data, give rise to hotly debated issues of privacy, security, and control. One specific challenge is the sharing or public release of anonymized data without accidentally ...

2011

Hierarchical Routing Over Dynamic Wireless Networks

Suhas Diggavi, Matthias Grossglauser

The topology of a mobile wireless network changes over time. Maintaining routes between all nodes requires the continuous transmission of control information, which consumes precious power and bandwidth resources. Many routing protocols have been developed ...

Wiley-Blackwell2015

Sub-Matrix Factorization for Real-Time Vote Prediction

Patrick Thiran, Matthias Grossglauser, Victor Kristof

We address the problem of predicting aggregate vote outcomes (e.g., national) from partial outcomes (e.g., regional) that are revealed sequentially. We combine matrix factorization techniques and generalized linear models (GLMs) to obtain a flexible, effic ...

2020

Mining Effective Strategies for Climate Change Communication

Francis Allan Charles Wilson Murray, Yurui Zhu, Matthias Grossglauser, Aswin Suresh, Lazar Milikic

With the goal of understanding effective strategies to communicate about climate change, we build interpretable models to rank tweets related to climate change with respect to the engagement they generate. Our models are based on the Bradley-Terry model of ...

2023

It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons

Matthias Grossglauser, Aswin Suresh

We propose an interpretable model to score the subjective bias present in documents, based only on their textual content. Our model is trained on pairs of revisions of the same Wikipedia article, where one version is more biased than the other. Although pr ...

2024

Online Collaborative Prediction of Regional Vote Results

Patrick Thiran, Matthias Grossglauser, Vincent Etter, Mohammad Emtiyaz Khan

We consider online predictions of vote results, where regions across a country vote on an issue under discussion. Such online predictions before and during the day of the vote are useful to media agencies, polling institutes, and political parties, e.g., t ...

IEEE2016

Self-Supervised Prototypical Transfer Learning for Few-Shot Classification

Matthias Grossglauser, Arnout Jan J Devos

Recent advances in transfer learning and few-shot learning largely rely on annotated data related to the goal task during (pre-)training. However, collecting sufficiently similar and annotated data is often infeasible. Building on advances in self-supervis ...

2020

Discovering Lobby-Parliamentarian Alignments through NLP

Matthias Grossglauser, Victor Kristof, Aswin Suresh

We discover alignments of views between interest groups (lobbies) and members of the European Parliament (MEPs) by automatically analyzing their texts. Specifically, we do so by collecting novel datasets of lobbies’ position papers and MEPs’ speeches, and ...

2024

Pairwise Comparisons with Flexible Time-Dynamics

Matthias Grossglauser, Lucas Maystre, Victor Kristof

Inspired by applications in sports where the skill of players or teams competing against each other varies over time, we propose a probabilistic model of pairwise-comparison outcomes that can capture a wide range of time dynamics. We achieve this by replac ...

ASSOC COMPUTING MACHINERY2019

Traveling Salesman in Reverse: Conditional Markov Entropy for Trajectory Segmentation

Patrick Thiran, Matthias Grossglauser, Mohamed Kafsi

We are interested in inferring the set of waypoints (or intermediate destinations) of a mobility trajectory in the absence of timing information. We find that, by mining a dataset of real mobility traces, computing the entropy of conditional Markov traject ...

IEEE2015

On the Performance of Percolation Graph Matching

Matthias Grossglauser, Lyudmila Yartseva

Graph matching is a generalization of the classic graph isomorphism problem. By using only their structures a graph-matching algorithm finds a map between the vertex sets of two similar graphs. This has applications in the de-anonymization of social and in ...

ACM2013

Cumulants of Hawkes Processes are Robust to Observation Noise

Patrick Thiran, Matthias Grossglauser, Negar Kiyavash, Seyed Jalal Etesami, William Trouleau

Multivariate Hawkes processes (MHPs) are widely used in a variety of fields to model the occurrence of causally related discrete events in continuous time. Most state-of-the-art approaches address the problem of learning MHPs from perfect traces without no ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

War of Words: The Competitive Dynamics of Legislative Processes

Patrick Thiran, Matthias Grossglauser, Victor Kristof

A body of law is an example of a dynamic corpus of text documents that are jointly maintained by a group of editors who compete and collaborate in complex constellations. Our goal is to develop predictive models for this process, thereby shedding light on ...

ACM / IW3C2 (International World Wide Web Conference Committee)2020

MobiRoute: Routing towards a Mobile Sink for Improving Lifetime in Sensor Networks

Jean-Pierre Hubaux, Matthias Grossglauser, Jun Luo, Jacques Panchard

Improving network lifetime is an important issue involved in every aspect of the design and deployment of wireless sensor networks. There is a recent research trend of studying the application of a mobile sink to transport (rather than let the sensor nodes ...

2006

The Player Kernel: Learning Team Strengths Based on Implicit Player Contributions

Matthias Grossglauser, Lucas Maystre, Victor Kristof

In this work, we draw attention to a connection between skill-based models of game outcomes and Gaussian process classification models. The Gaussian process perspective enables a) a principled way of dealing with uncertainty and b) rich models, specified t ...

2016

Densification Arising from Sampling Fixed Graphs

Matthias Grossglauser, Pedram Pedarsani

During the past decade, a number of different studies have identified several peculiar properties of networks that arise from a diverse universe, ranging from social to computer networks. A recently observed feature is known as network densification, which ...

ACM2008

The Entropy of Conditional Markov Trajectories

Patrick Thiran, Matthias Grossglauser, Mohamed Kafsi

To quantify the randomness of Markov trajectories with fixed initial and final states, Ekroot and Cover proposed a closed-form expression for the entropy of trajectories of an irreducible finite state Markov chain. Numerous applications, including the stud ...

2013

Uncovering Latent Behaviors in Ant Colonies

Patrick Thiran, Matthias Grossglauser, Laurent Keller, Mohamed Kafsi

Many biological systems exhibit collective behaviors that strengthen their adaptability to their environment, compared to more solitary species. Describing these behaviors is challenging yet necessary in order to understand these biological systems. We pro ...

SIAM2016

Can Who-Edits-What Predict Edit Survival?

Matthias Grossglauser, Lucas Maystre, Victor Kristof

As the number of contributors to online peer-production systems grows, it becomes increasingly important to predict whether the edits that users make will eventually be beneficial to the project. Existing solutions either rely on a user reputation system o ...

ACM2018