Concept
Couplage (théorie des graphes)
Publications associées (189)
A Distributed Augmenting Path Approach for the Bottleneck Assignment Problem
We develop an algorithm to solve the bottleneck assignment problem (BAP) that is amenable to having computation distributed over a network of agents. This consists of exploring how each component of the algorithm can be distributed, with a focus on one com ...
Piscataway2024Equivariant Neural Architectures for Representing and Generating Graphs
Graph machine learning offers a powerful framework with natural applications in scientific fields such as chemistry, biology and material sciences. By representing data as a graph, we encode the prior knowledge that the data is composed of a set of entitie ...
EPFL2023A full characterization of invariant embeddability of unimodular planar graphs
When can a unimodular random planar graph be drawn in the Euclidean or the hyperbolic plane in a way that the distribution of the random drawing is isometry-invariant? This question was answered for one-ended unimodular graphs in Benjamini and Timar, using ...
WILEY2023Beyond worst-case analysis, with or without predictions
In this thesis we design online combinatorial optimization algorithms for beyond worst-case analysis settings.In the first part, we discuss the online matching problem and prove that, in the edge arrival model, no online algorithm can achieve a competitive ...
EPFL2023Modeling and Optimization of Ridesplitting Operations
Ridesourcing has driven a lot of attention in recent years with the expansion of companies like Uber, Lift, and many others around the world. Companies use mobile applications connected through the internet to match drivers and their passengers real-time. ...
EPFL2023Streaming and Matching Problems with Submodular Functions
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 ...
EPFL2022Space-Efficient Representations of Graphs
With the increasing prevalence of massive datasets, it becomes important to design algorithmic techniques for dealing with scenarios where the input to be processed does not fit in the memory of a single machine. Many highly successful approaches have emer ...
EPFL2022SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
Nathanaël Perraudin, Andreas Loukas, Karolis Martinkus
We approach the graph generation problem from a spectral perspective by first generating the dominant parts of the graph Laplacian spectrum and then building a graph matching these eigenvalues and eigenvectors. Spectral conditioning allows for direct model ...
JMLR-JOURNAL MACHINE LEARNING RESEARCH2022Planted matching problems on random hypergraphs
Lenka Zdeborová, Anshul Toshniwal, Gabriele Sicuro
We consider the problem of inferring a matching hidden in a weighted random k-hypergraph. We assume that the hyperedges' weights are random and distributed according to two different densities conditioning on the fact that they belong to the hidden matchin ...
2022Tight Vector Bin Packing with Few Small Items via Fast Exact Matching in Multigraphs
Adam Teodor Polak, Alexandra Anna Lassota
We solve the Bin Packing problem in O^*(2^k) time, where k is the number of items less or equal to one third of the bin capacity. This parameter measures the distance from the polynomially solvable case of only large (i.e., greater than one third) items. O ...
Schloss Dagstuhl – Leibniz-Zentrum fur Informatik2022