16 citations · 26 across the 10 of their papers we have counts for
6 papers · 1 filter
Exchange-Based Diffusion in Hb-Graphs: Highlighting Complex Relationships
Xavier Ouvrard, Jean-Marie Le Goff, Stephane Marchand-Maillet
Most networks tend to show complex and multiple relationships between entities. Networks are usually modeled by graphs or hypergraphs; nonetheless a given entity can occur many tim…
Hypergraph Modeling and Visualisation of Complex Co-occurence Networks
Xavier Ouvrard, Jean-Marie Le Goff, Stephane Marchand-Maillet
Finding inherent or processed links within a dataset allows to discover potential knowledge. The main contribution of this article is to define a global framework that enables opti…
On Adjacency and e-Adjacency in General Hypergraphs: Towards a New e-Adjacency Tensor
Xavier Ouvrard, Jean-Marie Le Goff, Stephane Marchand-Maillet
In graphs, the concept of adjacency is clearly defined: it is a pairwise relationship between vertices. Adjacency in hypergraphs has to integrate hyperedge multi-adicity: the conce…
Structured nonlinear variable selection
Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet
We investigate structured sparsity methods for variable selection in regression problems where the target depends nonlinearly on the inputs. We focus on general nonlinear functions…
Adjacency and Tensor Representation in General Hypergraphs.Part 2: Multisets, Hb-graphs and Related e-adjacency Tensors
Xavier Ouvrard, Jean-Marie Le Goff, Stephane Marchand-Maillet
HyperBagGraphs (hb-graphs as short) extend hypergraphs by allowing the hyperedges to be multisets. Multisets are composed of elements that have a multiplicity. When this multiplici…
Large-scale Nonlinear Variable Selection via Kernel Random Features
Magda Gregorová, Jason Ramapuram, Alexandros Kalousis +1
We propose a new method for input variable selection in nonlinear regression. The method is embedded into a kernel regression machine that can model general nonlinear functions, no…