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Matthias Grossglauser

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Publications associées (58)

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

Just Sort It! A Simple and Effective Approach to Active Preference Learning

Matthias Grossglauser, Lucas Maystre

We address the problem of learning a ranking by using adaptively chosen pairwise comparisons. Our goal is to recover the ranking accurately but to sample the comparisons sparingly. If all comparison outcomes are consistent with the ranking, the optimal sol ...

2017

ChoiceRank: Identifying Preferences from Node Traffic in Networks

Matthias Grossglauser, Lucas Maystre

Understanding how users navigate in a network is of high interest in many applications. We consider a setting where only aggregate node-level traffic is observed and tackle the task of learning edge transition probabilities. We cast it as a preference lear ...

2017

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

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

Uncovering Latent Behaviors in Ant Colonies

Patrick Thiran, Laurent Keller, Matthias Grossglauser, Mohamed Kafsi, Raphaël Braunschweig

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

PROPER: global protein interaction network alignment through percolation matching

Matthias Grossglauser, Seyed Hamed Hassani, Ehsan Kazemi, Hasan Pezeshgi Modarres

Background The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological know ...

2016

Collaborative Recurrent Neural Networks for Dynamic Recommender Systems

Matthias Grossglauser, Lucas Maystre, Young Jun Ko

Modern technologies enable us to record sequences of online user activity at an unprecedented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating-prediction paradigm, ignoring temporal ...

2016

Growing a Graph Matching from a Handful of Seeds

Matthias Grossglauser, Seyed Hamed Hassani, Ehsan Kazemi

In many graph–mining problems, two networks from different domains have to be matched. In the absence of reliable node attributes, graph matching has to rely on only the link structures of the two networks, which amounts to a generalization of the classic ...

Assoc Computing Machinery2015

Fast and Accurate Inference of Plackett-Luce Models

Matthias Grossglauser, Lucas Maystre

We show that the maximum-likelihood (ML) estimate of models derived from Luce’s choice axiom (e.g., the Plackett–Luce model) can be expressed as the stationary distribution of a Markov chain. This conveys insight into several recently proposed spectral inf ...

2015

Hierarchical Routing Over Dynamic Wireless Networks

Dominique Florian Tschopp, Matthias Grossglauser, Suhas Diggavi

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

When Can Two Unlabeled Networks Be Aligned Under Partial Overlap?

Matthias Grossglauser, Ehsan Kazemi, Lyudmila Yartseva

Network alignment refers to the problem of matching the vertex sets of two unlabeled graphs, which can be viewed as a generalization of the classic graph isomorphism problem. Network alignment has applications in several fields, including social network an ...

2015

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

Mining Democracy

Patrick Thiran, Matthias Grossglauser, Vincent Etter, Julien Pierre Sacha Herzen

Switzerland has a long tradition of direct democracy, which makes it an ideal laboratory for research on real-world politics. Similar to recent open government initiatives launched worldwide, the Swiss government regularly releases datasets related to stat ...

2014

Data-driven healthcare: from patterns to actions

Matthias Grossglauser

The era of big data opens up new opportunities in personalised medicine, preventive care, chronic disease management and in telemonitoring and managing of patients with implanted devices. The rich data accumulating within online services and internet compa ...

Sage Publications Ltd2014

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

Where to go from here? Mobility prediction from instantaneous information

Patrick Thiran, Matthias Grossglauser, Mohamed Kafsi, Vincent Etter, Ehsan Kazemi

We present the work that allowed us to win the Next-Place Prediction task of the Nokia Mobile Data Challenge. Using data collected from the smartphones of 80 users, we explore the characteristics of their mobility traces. We then develop three families of ...

Elsevier Science Bv2013

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

Launch Hard or Go Home! Predicting the Success of Kickstarter Campaigns

Patrick Thiran, Matthias Grossglauser, Vincent Etter

Crowdfunding websites such as Kickstarter are becoming increasingly popular, allowing project creators to raise hundreds of millions of dollars every year. However, only one out of two Kickstarter campaigns reaches its funding goal and is successful. It is ...

ACM2013

Mitigating Epidemics through Mobile Micro-measures

Patrick Thiran, Matthias Grossglauser, Mohamed Kafsi, Lucas Maystre, Ehsan Kazemi, Lyudmila Yartseva

2013

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