Mathieu Blondel

CoRR, 2024

The Elements of Differentiable Programming.

[BibT_eX]

[DOI]

Vincent Roulet

CoRR, 2024

Implicit Diffusion: Efficient Optimization through Stochastic Sampling.

[BibT_eX]

[DOI]

Courtney Paquette

Quentin Berthet

CoRR, 2024

Direct Language Model Alignment from Online AI Feedback.

[BibT_eX]

[DOI]

CoRR, 2024

How do Transformers Perform In-Context Autoregressive Learning ?

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Decoding-time Realignment of Language Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Dual Gauss-Newton Directions for Deep Learning.

[BibT_eX]

[DOI]

Vincent Roulet

CoRR, 2023

Fast, Differentiable and Sparse Top-k: a Convex Analysis Perspective.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Sparsity-Constrained Optimal Transport.

[BibT_eX]

[DOI]

Tianlin Liu

Joan Puigcerver

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Sparse Continuous Distributions and Fenchel-Young Losses.

[BibT_eX]

[DOI]

Mário A. T. Figueiredo

J. Mach. Learn. Res., 2022

Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Cutting Some Slack for SGD with Adaptive Polyak Stepsizes.

[BibT_eX]

[DOI]

CoRR, 2022

Learning Energy Networks with Generalized Fenchel-Young Losses.

[BibT_eX]

[DOI]

Robert Dadashi

Léonard Hussenot

Matthieu Geist

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient and Modular Implicit Differentiation.

[BibT_eX]

[DOI]

Fabian Pedregosa

Jean-Philippe Vert

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sinkformers: Transformers with Doubly Stochastic Attention.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Self-Supervised Learning of Audio Representations From Permutations With Differentiable Ranking.

[BibT_eX]

[DOI]

IEEE Signal Process. Lett., 2021

Momentum Residual Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Differentiable Divergences Between Time Series.

[BibT_eX]

[DOI]

Arthur Mensch

Jean-Philippe Vert

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Learning with Fenchel-Young losses.

[BibT_eX]

[DOI]

André F. T. Martins

J. Mach. Learn. Res., 2020

Learning with Differentiable Perturbed Optimizers.

[BibT_eX]

[DOI]

CoRR, 2020

Learning with Differentiable Pertubed Optimizers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fast Differentiable Sorting and Ranking.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Implicit differentiation of Lasso-type models for hyperparameter optimization.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Structured Prediction with Projection Oracles.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Geometric Losses for Distributional Learning.

[BibT_eX]

[DOI]

Arthur Mensch

Gabriel Peyré

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning Classifiers with Fenchel-Young Losses: Generalized Entropies, Margins, and Algorithms.

[BibT_eX]

[DOI]

André F. T. Martins

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Blind source separation with optimal transport non-negative matrix factorization.

[BibT_eX]

[DOI]

EURASIP J. Adv. Signal Process., 2018

SparseMAP: Differentiable Sparse Structured Inference.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

Differentiable Dynamic Programming for Structured Prediction and Attention.

[BibT_eX]

[DOI]

Arthur Mensch

Bharath Bhushan Damodaran

Proceedings of the 35th International Conference on Machine Learning, 2018

Large Scale Optimal Transport and Mapping Estimation.

[BibT_eX]

[DOI]

Vivien Seguy

Proceedings of the 6th International Conference on Learning Representations, 2018

Smooth and Sparse Optimal Transport.

[BibT_eX]

[DOI]

Vivien Seguy

Antoine Rolet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Scaling Locally Linear Embedding.

[BibT_eX]

[DOI]

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

A Regularized Framework for Sparse and Structured Neural Attention.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Multi-output Polynomial Networks and Factorization Machines.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

SVD-Based Screening for the Graphical Lasso.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Soft-DTW: a Differentiable Loss Function for Time-Series.

[BibT_eX]

[DOI]

Marco Cuturi

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Higher-Order Factorization Machines.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Polynomial Networks and Factorization Machines: New Insights and Efficient Training Algorithms.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Convex Factorization Machines.

[BibT_eX]

[DOI]

Akinori Fujino

Naonori Ueda

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries.

[BibT_eX]

[DOI]

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

Large-Scale Multiclass Support Vector Machine Training via Euclidean Projection onto the Simplex.

[BibT_eX]

[DOI]

Akinori Fujino

Naonori Ueda

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion.

[BibT_eX]

[DOI]

Yotaro Kubo

Naonori Ueda

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Block coordinate descent algorithms for large-scale sparse multiclass classification.

[BibT_eX]

[DOI]

Mach. Learn., 2013

API design for machine learning software: experiences from the scikit-learn project.

[BibT_eX]

[DOI]

CoRR, 2013

Learning non-linear classifiers with a sparsity constraint using L1 regularization.

[BibT_eX]

[DOI]

Proceedings of the 28th Annual ACM Symposium on Applied Computing, 2013

2011

Scikit-learn: Machine Learning in Python.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2011

Tackling class imbalance and data scarcity in literature-based gene function annotation.

[BibT_eX]

[DOI]

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

Application of Semantic Kernels to Literature-Based Gene Function Annotation.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science - 14th International Conference, 2011

2010

Unsupervised Learning of Stroke Tagger for Online Kanji Handwriting Recognition.

[BibT_eX]

[DOI]