Extended Formulations from Communication Protocols in Output-Efficient Time

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Random walks and forbidden minors III: poly(d epsilon(-1))-time partition oracles for minor-free graph classes

Akash Kumar

Consider the family of bounded degree graphs in any minor-closed family (such as planar graphs). Let d be the degree bound and n be the number of vertices of such a graph. Graphs in these classes have hyperfinite decompositions, where, one removes a small ...

IEEE COMPUTER SOC2022

fGOT: Graph Distances Based on Filters and Optimal Transport

Pascal Frossard, Mireille El Gheche, Hermina Petric Maretic, Giovanni Chierchia

Graph comparison deals with identifying similarities and dissimilarities between graphs. A major obstacle is the unknown alignment of graphs, as well as the lack of accurate and inexpensive comparison metrics. In this work we introduce the filter graph dis ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks

Karl Aberer, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong

Graph neural networks take node features and graph structure as input to build representations for nodes and graphs. While there are a lot of focus on GNN models, understanding the impact of node features and graph structure to GNN performance has received ...

ELSEVIER2022

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Paul Thierry Yves Rolland

One of the main goal of Artificial Intelligence is to develop models capable of providing valuable predictions in real-world environments. In particular, Machine Learning (ML) seeks to design such models by learning from examples coming from this same envi ...

EPFL2022

Reduced representations of complexes, signals, and multifiltrations

Celia Camille Hacker

The field of computational topology has developed many powerful tools to describe the shape of data, offering an alternative point of view from classical statistics. This results in a variety of complex structures that are not always directly amenable for ...

EPFL2022

Streaming and Matching Problems with Submodular Functions

Paritosh Garg

Submodular functions are a widely studied topic in theoretical computer science. They have found several applications both theoretical and practical in the fields of economics, combinatorial optimization and machine learning. More recently, there have also ...

EPFL2022

Representing graphs through data with learning and optimal transport

Hermina Petric Maretic

Graphs offer a simple yet meaningful representation of relationships between data. This representation is often used in machine learning algorithms in order to incorporate structural or geometric information about data. However, it can also be used in an i ...

EPFL2021

Representation Learning for Multi-relational Data

Eda Bayram

Recent years have witnessed a rise in real-world data captured with rich structural information that can be better depicted by multi-relational or heterogeneous graphs. However, research on relational representation learning has so far mostly focused on th ...

EPFL2021

Multilayer Graph Clustering With Optimized Node Embedding

Pascal Frossard, Mireille El Gheche

We are interested in multilayer graph clustering, which aims at dividing the graph nodes into categories or communities. To do so, we propose to learn a clustering-friendly embedding of the graph nodes by solving an optimization problem that involves a fid ...

IEEE2021

Integrating advanced discrete choice models in mixed integer linear optimization

Michel Bierlaire, Meritxell Pacheco Paneque, Bernard Gendron

In many transportation systems, a mismatch between the associated design and planning decisions and the demand is typically encountered. A tailored system is not only appealing to operators, which could have a better knowledge of their operational costs, b ...

PERGAMON-ELSEVIER SCIENCE LTD2021

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