Követés
Mathieu Blondel
Mathieu Blondel
E-mail megerősítve itt: google.com - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
922842011
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
33842013
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
6932017
Higher-order factorization machines
M Blondel, A Fujino, N Ueda, M Ishihata
Advances in Neural Information Processing Systems 29, 2016
2412016
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
2322018
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
1952020
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
1922021
Fast differentiable sorting and ranking
M Blondel, O Teboul, Q Berthet, J Djolonga
International Conference on Machine Learning, 950-959, 2020
1922020
Smooth and sparse optimal transport
M Blondel, V Seguy, A Rolet
Proceedings of the Twenty-First International Conference on Artificial …, 2018
1852018
Scikit-learn: Machine learning in Python
F Pedegrosa, G Varoquaux, A Gramfort, V Michel, B Thirion, O Grisel, ...
Journal of Machine Learning Research 12, 2825-2830, 2011
1672011
Differentiable dynamic programming for structured prediction and attention
A Mensch, M Blondel
Proceedings of the 35th International Conference on Machine Learning (ICML …, 2018
1572018
SparseMAP: Differentiable sparse structured inference
V Niculae, AFT Martins, M Blondel, C Cardie
Proceedings of the 35th International Conference on Machine Learning (ICML …, 2018
1272018
A regularized framework for sparse and structured neural attention
V Niculae, M Blondel
Advances in neural information processing systems 30, 2017
1152017
Learning with Fenchel-Young losses
M Blondel, AFT Martins, V Niculae
arXiv preprint arXiv:1901.02324, 2019
1142019
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
992016
Block coordinate descent algorithms for large-scale sparse multiclass classification
M Blondel, K Seki, K Uehara
Machine Learning 93 (1), 31-52, 2013
802013
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
692020
A ranking approach to genomic selection
M Blondel, A Onogi, H Iwata, N Ueda
PloS one 10 (6), e0128570, 2015
632015
Momentum residual neural networks
ME Sander, P Ablin, M Blondel, G Peyré
International Conference on Machine Learning, 9276-9287, 2021
602021
Differentiable divergences between time series
M Blondel, A Mensch, JP Vert
International Conference on Artificial Intelligence and Statistics, 3853-3861, 2021
542021
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