Publications by Victor Kristof

Chronology and Sequence of Permanent Tooth Eruption in a Multi-Ethnic Urban Population

Objective: This study aimed to evaluate the mean age of eruption of permanent teeth and their clinical emergence sequence in a longitudinal sample of children from a multi-ethnic urban population. Methods: A total of 854 children (413 females and 441 males ...

MDPI AG2025

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

Discrete-Choice Mining of Social Processes

Victor Kristof

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

EPFL2021

War of Words II: Enriched Models of Law-Making Processes

Patrick Thiran, Matthias Grossglauser, Victor Kristof, Aswin Suresh

The European Union law-making process is an instance of a peer- production system. We mine a rich dataset of law edits and intro- duce models predicting their adoption by parliamentary committees. Edits are proposed by parliamentarians, and they can be in ...

ACM2021

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

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

Pairwise Comparisons with Flexible Time-Dynamics

Matthias Grossglauser, Victor Kristof, Lucas Maystre

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

A User Study of Perceived Carbon Footprint

Patrick Thiran, Matthias Grossglauser, Victor Kristof, Robin Adrien Zbinden, Lucas Maystre, Valentin Quelquejay-Leclère

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

Can Who-Edits-What Predict Edit Survival?

Matthias Grossglauser, Victor Kristof, Lucas Maystre

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

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

Matthias Grossglauser, Victor Kristof, Lucas Maystre

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