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Mathieu Blondel
Mathieu Blondel
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Cited by
Year
Scikit-learn: Machine learning in Python
F Pedregosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ...
the Journal of machine Learning research 12, 2825-2830, 2011
1024742011
API design for machine learning software: experiences from the scikit-learn project
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
arXiv preprint arXiv:1309.0238, 2013
37492013
Soft-DTW: a differentiable loss function for time-series
M Cuturi, M Blondel
Proceedings of the 34th International Conference on Machine Learning, 894--903, 2017
8352017
Large-scale optimal transport and mapping estimation
V Seguy, BB Damodaran, R Flamary, N Courty, A Rolet, M Blondel
International Conference on Learning Representations, 2018
2642018
Higher-order factorization machines
M Blondel, A Fujino, N Ueda, M Ishihata
Advances in neural information processing systems 29, 2016
2632016
Efficient and modular implicit differentiation
M Blondel, Q Berthet, M Cuturi, R Frostig, S Hoyer, F Llinares-López, ...
Advances in neural information processing systems, 2021
2602021
Learning with differentiable pertubed optimizers
Q Berthet, M Blondel, O Teboul, M Cuturi, JP Vert, F Bach
Advances in neural information processing systems 33, 9508-9519, 2020
2482020
Fast differentiable sorting and ranking
M Blondel, O Teboul, Q Berthet, J Djolonga
International Conference on Machine Learning, 950-959, 2020
2412020
Smooth and sparse optimal transport
M Blondel, V Seguy, A Rolet
Proceedings of the Twenty-First International Conference on Artificial …, 2018
2062018
Differentiable dynamic programming for structured prediction and attention
A Mensch, M Blondel
Proceedings of the 35th International Conference on Machine Learning (ICML …, 2018
1612018
SparseMAP: Differentiable sparse structured inference
V Niculae, AFT Martins, M Blondel, C Cardie
Proceedings of the 35th International Conference on Machine Learning (ICML …, 2018
1382018
Learning with Fenchel-Young losses
M Blondel, AFT Martins, V Niculae
arXiv preprint arXiv:1901.02324, 2019
1362019
A regularized framework for sparse and structured neural attention
V Niculae, M Blondel
Advances in neural information processing systems 30, 2017
1242017
Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms
M Blondel, M Ishihata, A Fujino, N Ueda
Proceedings of the 33rd International Conference on Machine Learning, 850–858, 2016
1012016
Block coordinate descent algorithms for large-scale sparse multiclass classification
M Blondel, K Seki, K Uehara
Machine Learning 93 (1), 31-52, 2013
822013
Direct language model alignment from online ai feedback
S Guo, B Zhang, T Liu, T Liu, M Khalman, F Llinares, A Rame, T Mesnard, ...
arXiv preprint arXiv:2402.04792, 2024
772024
Implicit differentiation of lasso-type models for hyperparameter optimization
Q Bertrand, Q Klopfenstein, M Blondel, S Vaiter, A Gramfort, J Salmon
International Conference on Machine Learning, 810-821, 2020
762020
Momentum residual neural networks
ME Sander, P Ablin, M Blondel, G Peyré
International Conference on Machine Learning, 9276-9287, 2021
712021
A ranking approach to genomic selection
M Blondel, A Onogi, H Iwata, N Ueda
PloS one 10 (6), e0128570, 2015
702015
Sinkformers: Transformers with doubly stochastic attention
ME Sander, P Ablin, M Blondel, G Peyré
International Conference on Artificial Intelligence and Statistics, 3515-3530, 2022
692022
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