Search Results for author: Marco Saerens

Found 12 papers, 0 papers with code

Relative Entropy-Regularized Optimal Transport on a Graph: a new algorithm and an experimental comparison

no code implementations23 Aug 2021 Sylvain Courtain, Guillaume Guex, Ilkka Kivimaki, Marco Saerens

Following [21, 23], the present work investigates a new relative entropy-regularized algorithm for solving the optimal transport on a graph problem within the randomized shortest paths formalism.

Sparse Randomized Shortest Paths Routing with Tsallis Divergence Regularization

no code implementations1 Jul 2020 Pierre Leleux, Sylvain Courtain, Guillaume Guex, Marco Saerens

This work elaborates on the important problem of (1) designing optimal randomized routing policies for reaching a target node t from a source note s on a weighted directed graph G and (2) defining distance measures between nodes interpolating between the least cost (based on optimal movements) and the commute-cost (based on a random walk on G), depending on a temperature parameter T. To this end, the randomized shortest path formalism (RSP, [2, 99, 124]) is rephrased in terms of Tsallis divergence regularization, instead of Kullback-Leibler divergence.

Node Clustering

Randomized Shortest Paths with Net Flows and Capacity Constraints

no code implementations4 Oct 2019 Sylvain Courtain, Pierre Leleux, Ilkka Kivimaki, Guillaume Guex, Marco Saerens

The framework assumes a unit flow injected into a source node and collected from a target node with flows minimizing the expected transportation cost, together with a relative entropy regularization term.

Node Clustering

Covariance and Correlation Kernels on a Graph in the Generalized Bag-of-Paths Formalism

no code implementations8 Feb 2019 Guillaume Guex, Sylvain Courtain, Marco Saerens

This work derives closed-form expressions computing the expectation of co-presence and of number of co-occurrences of nodes on paths sampled from a network according to general path weights (a bag of paths).

General Classification

A Constrained Randomized Shortest-Paths Framework for Optimal Exploration

no code implementations12 Jul 2018 Bertrand Lebichot, Guillaume Guex, Ilkka Kivimäki, Marco Saerens

The present work extends the randomized shortest-paths framework (RSP), interpolating between shortest-path and random-walk routing in a network, in three directions.

Randomized Optimal Transport on a Graph: framework and new distance measures

no code implementations7 Jun 2018 Guillaume Guex, Ilkka Kivimäki, Marco Saerens

When the temperature is low, this formalism is shown to be equivalent to a relaxation of the optimal transport problem on a network where paths carry a flow between two discrete distributions on nodes.

An experimental study of graph-based semi-supervised classification with additional node information

no code implementations24 May 2017 Bertrand Lebichot, Marco Saerens

The volume of data generated by internet and social networks is increasing every day, and there is a clear need for efficient ways of extracting useful information from them.

14 Classification +2

Combining Manual and Automatic Prosodic Annotation for Expressive Speech Synthesis

no code implementations LREC 2016 S Brognaux, rine, Thomas Fran{\c{c}}ois, Marco Saerens

A major issue of existing approaches is that they usually rely on a manual annotation in expressive styles, which tends to be rather subjective.

Expressive Speech Synthesis TAG

A bag-of-paths framework for network data analysis

no code implementations27 Feb 2013 Kevin Françoisse, Ilkka Kivimäki, Amin Mantrach, Fabrice Rossi, Marco Saerens

This probability captures a notion of relatedness between nodes of the graph: two nodes are considered as highly related when they are connected by many, preferably low-cost, paths.

Developments in the theory of randomized shortest paths with a comparison of graph node distances

no code implementations7 Dec 2012 Ilkka Kivimäki, Masashi Shimbo, Marco Saerens

In particular, we see that the results obtained with the free energy distance are among the best in all the experiments.

Node Clustering

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