ML Anthology
Authors
Search
About
d'Alché-Buc, Florence
20 publications
ICLR
2025
Restyling Unsupervised Concept Based Interpretable Networks with Generative Models
Jayneel Parekh
,
Quentin Bouniot
,
Pavlo Mozharovskyi
,
Alasdair Newson
,
Florence d'Alché-Buc
ICLR
2025
Tailoring Mixup to Data for Calibration
Quentin Bouniot
,
Pavlo Mozharovskyi
,
Florence d'Alché-Buc
NeurIPS
2025
The Quest for the GRAph Level autoEncoder (GRALE)
Paul Krzakala
,
Gabriel Melo
,
Charlotte Laclau
,
Florence d'Alché-Buc
,
Rémi Flamary
ICMLW
2024
A Framework for Differentiable Supervised Graph Prediction
Paul Krzakala
,
Junjie Yang
,
Rémi Flamary
,
Florence d'Alché-Buc
,
Charlotte Laclau
,
Matthieu Labeau
TMLR
2024
A Pseudo-Metric Between Probability Distributions Based on Depth-Trimmed Regions
Guillaume Staerman
,
Pavlo Mozharovskyi
,
Pierre Colombo
,
Stephan Clémençon
,
Florence d'Alché-Buc
NeurIPS
2024
Any2Graph: Deep End-to-End Supervised Graph Prediction with an Optimal Transport Loss
Paul Krzakala
,
Junjie Yang
,
Rémi Flamary
,
Florence d'Alché-Buc
,
Charlotte Laclau
,
Matthieu Labeau
TMLR
2024
Exploiting Edge Features in Graph-Based Learning with Fused Network Gromov-Wasserstein Distance
Junjie Yang
,
Matthieu Labeau
,
Florence d'Alché-Buc
TMLR
2023
Fast Kernel Methods for Generic Lipschitz Losses via $p$-Sparsified Sketches
Tamim El Ahmad
,
Pierre Laforgue
,
Florence d'Alché-Buc
NeurIPS
2022
Listen to Interpret: Post-Hoc Interpretability for Audio Networks with NMF
Jayneel Parekh
,
Sanjeel Parekh
,
Pavlo Mozharovskyi
,
Florence d'Alché-Buc
,
Gaël Richard
JMLR
2022
Vector-Valued Least-Squares Regression Under Output Regularity Assumptions
Luc Brogat-Motte
,
Alessandro Rudi
,
Céline Brouard
,
Juho Rousu
,
Florence d'Alché-Buc
NeurIPS
2021
A Framework to Learn with Interpretation
Jayneel Parekh
,
Pavlo Mozharovskyi
,
Florence d'Alché-Buc
JMLR
2021
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program)
Joelle Pineau
,
Philippe Vincent-Lamarre
,
Koustuv Sinha
,
Vincent Lariviere
,
Alina Beygelzimer
,
Florence d'Alche-Buc
,
Emily Fox
,
Hugo Larochelle
ICMLW
2019
A Functional Extension of Multi-Output Learning
Alex Lambert
,
Romain Brault
,
Zoltan Szabo
,
Florence d'Alche-Buc
NeurIPS
2018
A Structured Prediction Approach for Label Ranking
Anna Korba
,
Alexandre Garcia
,
Florence d'Alché-Buc
MLJ
2018
Output Fisher Embedding Regression
Moussab Djerrab
,
Alexandre Garcia
,
Maxime Sangnier
,
Florence d'Alché-Buc
JMLR
2016
Input Output Kernel Regression: Supervised and Semi-Supervised Structured Output Prediction with Operator-Valued Kernels
Céline Brouard
,
Marie Szafranski
,
Florence d'Alché-Buc
NeurIPS
2016
Joint Quantile Regression in Vector-Valued RKHSs
Maxime Sangnier
,
Olivier Fercoq
,
Florence d'Alché-Buc
MLJ
2015
Operator-Valued Kernel-Based Vector Autoregressive Models for Network Inference
Néhémy Lim
,
Florence d'Alché-Buc
,
Cédric Auliac
,
George Michailidis
NeurIPS
2003
Dynamical Modeling with Kernels for Nonlinear Time Series Prediction
Liva Ralaivola
,
Florence d'Alché-Buc
NeurIPS
2001
Semi-Supervised MarginBoost
Florence d'Alché-Buc
,
Yves Grandvalet
,
Christophe Ambroise