40 citations
- Laboratoire Traitement et Communication de l’InformationFR14 papers
- KU LeuvenBE13 papers
- Institut Polytechnique de ParisFR7 papers
- Laboratoire Traitement du Signal et de l'ImageFR4 papers
- Télécom ParisFR4 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Laboratoire d’Informatique et SystèmesFR3 papers
- Centre BorelliFR2 papers
- IBM (France)FR2 papers
- Institut national de recherche en sciences et technologies du numériqueFR2 papers
- Kyoto UniversityJP2 papers
- Laboratoire des signaux et systèmesFR2 papers
7 papers · 1 filter
On the choice of the optimal temporal support for audio classification with Pre-trained embeddings
Aurian Quelennec, Michel Olvera, Geoffroy Peeters +1
Current state-of-the-art audio analysis systems rely on pre-trained embedding models, often used off-the-shelf as (frozen) feature extractors. Choosing the best one for a set of ta…
Polyhedral approach to weighted connected matchings in general graphs
Phillippe Samer, Phablo F. S. Moura
A connected matching in a graph G consists of a set of pairwise disjoint edges whose covered vertices induce a connected subgraph of G. While finding a connected matching of maximu…
Multivariate Singular Spectrum Analysis by Robust Diagonalwise Low-Rank Approximation
Fabio Centofanti, Mia Hubert, Biagio Palumbo +1
Multivariate Singular Spectrum Analysis (MSSA) is a powerful and widely used nonparametric method for multivariate time series, which allows the analysis of complex temporal data f…
Approximations for the Steiner Multicycle Problem
Cristina G. Fernandes, Carla N. Lintzmayer, Phablo F. S. Moura
The Steiner Multicycle problem consists of, given a complete graph, a weight function on its vertices, and a collection of pairwise disjoint non-unitary sets called terminal sets,…
Transfer Learning and Bias Correction with Pre-trained Audio Embeddings
Changhong Wang, Gaël Richard, Brian McFee
Deep neural network models have become the dominant approach to a large variety of tasks within music information retrieval (MIR). These models generally require large amounts of (…
Solving stochastic weak Minty variational inequalities without increasing batch size
Thomas Pethick, Olivier Fercoq, Puya Latafat +2
This paper introduces a family of stochastic extragradient-type algorithms for a class of nonconvex-nonconcave problems characterized by the weak Minty variational inequality (MVI)…