Fabian Pedregosa

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 60

Top Topics

Stochastic Gradient Descent

Machine Learning

Regression Methods

Top Venues

Publications

Sanjeev Raja, Ishan Amin, Fabian Pedregosa, Aditi S. Krishnapriyan
Stability-Aware Training of Neural Network Interatomic Potentials with Differentiable Boltzmann Estimators. CoRR (2024)
Eleni Triantafillou, Peter Kairouz, Fabian Pedregosa, Jamie Hayes, Meghdad Kurmanji, Kairan Zhao, Vincent Dumoulin, Júlio C. S. Jacques Júnior, Ioannis Mitliagkas, Jun Wan, Lisheng Sun-Hosoya, Sergio Escalera, Gintare Karolina Dziugaite, Peter Triantafillou, Isabelle Guyon
Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition. CoRR (2024)
Vincent Roulet, Atish Agarwala, Jean-Bastien Grill, Grzegorz Swirszcz, Mathieu Blondel, Fabian Pedregosa
Stepping on the Edge: Curvature Aware Learning Rate Tuners. CoRR (2024)
Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
When is Momentum Extragradient Optimal? A Polynomial-Based Analysis. Trans. Mach. Learn. Res. 2024 (2024)
Atish Agarwala, Fabian Pedregosa, Jeffrey Pennington
Second-order regression models exhibit progressive sharpening to the edge of stability. ICML (2023)
Vincent Roulet, Atish Agarwala, Fabian Pedregosa
On the Interplay Between Stepsize Tuning and Progressive Sharpening. CoRR (2023)
Courtney Paquette, Bart van Merriënboer, Elliot Paquette, Fabian Pedregosa
Halting Time is Predictable for Large Models: A Universality Property and Average-Case Analysis. Found. Comput. Math. 23 (2) (2023)
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. AISTATS (2023)
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
Efficient and Modular Implicit Differentiation. NeurIPS (2022)
Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov
GradMax: Growing Neural Networks using Gradient Information. ICLR (2022)
Baptiste Goujaud, Damien Scieur, Aymeric Dieuleveut, Adrien B. Taylor, Fabian Pedregosa
Super-Acceleration with Cyclical Step-sizes. AISTATS (2022)
Robert M. Gower, Mathieu Blondel, Nidham Gazagnadou, Fabian Pedregosa
Cutting Some Slack for SGD with Adaptive Polyak Stepsizes. CoRR (2022)
Paul Vicol, Jonathan Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse
On Implicit Bias in Overparameterized Bilevel Optimization. CoRR (2022)
Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
Only Tails Matter: Average-Case Universality and Robustness in the Convex Regime. CoRR (2022)
Atish Agarwala, Fabian Pedregosa, Jeffrey Pennington
Second-order regression models exhibit progressive sharpening to the edge of stability. CoRR (2022)
Paul Vicol, Jonathan P. Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse
On Implicit Bias in Overparameterized Bilevel Optimization. ICML (2022)
Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum. CoRR (2022)
Utku Evci, Max Vladymyrov, Thomas Unterthiner, Bart van Merriënboer, Fabian Pedregosa
GradMax: Growing Neural Networks using Gradient Information. CoRR (2022)
Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa
The Curse of Unrolling: Rate of Differentiating Through Optimization. NeurIPS (2022)
Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. CoRR (2022)
Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
Only tails matter: Average-Case Universality and Robustness in the Convex Regime. ICML (2022)
Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
Boosting Variational Inference With Locally Adaptive Step-Sizes. IJCAI (2021)
Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
Boosting Variational Inference With Locally Adaptive Step-Sizes. CoRR (2021)
Fartash Faghri, Cristina Vasconcelos, David J. Fleet, Fabian Pedregosa, Nicolas Le Roux
Bridging the Gap Between Adversarial Robustness and Optimization Bias. CoRR (2021)
Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
Efficient and Modular Implicit Differentiation. CoRR (2021)
Courtney Paquette, Kiwon Lee, Fabian Pedregosa, Elliot Paquette
SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality. COLT (2021)
Courtney Paquette, Kiwon Lee, Fabian Pedregosa, Elliot Paquette
SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality. CoRR (2021)
Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur
Average-case Acceleration for Bilinear Games and Normal Matrices. ICLR (2021)
Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Fabian Pedregosa
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. CoRR (2020)
Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux
On the interplay between noise and curvature and its effect on optimization and generalization. AISTATS (2020)
Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. ICML (2020)
Lukas Balles, Fabian Pedregosa, Nicolas Le Roux
The Geometry of Sign Gradient Descent. CoRR (2020)
Fabian Pedregosa, Damien Scieur
Average-case Acceleration Through Spectral Density Estimation. CoRR (2020)
Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur
Average-case Acceleration for Bilinear Games and Normal Matrices. CoRR (2020)
Damien Scieur, Fabian Pedregosa
Universal Asymptotic Optimality of Polyak Momentum. ICML (2020)
Fabian Pedregosa, Damien Scieur
Acceleration through spectral density estimation. ICML (2020)
Fabian Pedregosa, Geoffrey Négiar, Armin Askari, Martin Jaggi
Linearly Convergent Frank-Wolfe without Line-Search. AISTATS (2020)
Elena Kalinina, Fabian Pedregosa, Vittorio Iacovella, Emanuele Olivetti, Paolo Avesani
A Test for Shared Patterns in Cross-modal Brain Activation Analysis. CoRR (2019)
Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stéfan van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, C. J. Carey, Ilhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E. A. Quintero, Charles R. Harris, Anne M. Archibald, Antônio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt, SciPy 1. 0 Contributors
SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python. CoRR (2019)
Utku Evci, Fabian Pedregosa, Aidan N. Gomez, Erich Elsen
The Difficulty of Training Sparse Neural Networks. CoRR (2019)
Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux
Information matrices and generalization. CoRR (2019)
Fabian Pedregosa, Kilian Fatras, Mattia Casotto
Proximal Splitting Meets Variance Reduction. AISTATS (2019)
Fabian Pedregosa, Gauthier Gidel
Adaptive Three Operator Splitting. ICML (2018)
Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
Frank-Wolfe Splitting via Augmented Lagrangian Method. CoRR (2018)
Thomas Kerdreux, Fabian Pedregosa, Alexandre d'Aspremont
Frank-Wolfe with Subsampling Oracle. CoRR (2018)
Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
Improved asynchronous parallel optimization analysis for stochastic incremental methods. CoRR (2018)
Fabian Pedregosa, Gauthier Gidel
Adaptive Three Operator Splitting. CoRR (2018)
Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
Frank-Wolfe Splitting via Augmented Lagrangian Method. AISTATS (2018)
Thomas Kerdreux, Fabian Pedregosa, Alexandre d'Aspremont
Frank-Wolfe with Subsampling Oracle. ICML (2018)
Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods. J. Mach. Learn. Res. 19 (2018)
Aaron Meurer, Christopher P. Smith, Mateusz Paprocki, Ondrej Certík, Sergey B. Kirpichev, Matthew Rocklin, Amit Kumar, Sergiu Ivanov, Jason Keith Moore, Sartaj Singh, Thilina Rathnayake, Sean Vig, Brian E. Granger, Richard P. Muller, Francesco Bonazzi, Harsh Gupta, Shivam Vats, Fredrik Johansson, Fabian Pedregosa, Matthew J. Curry, Andy R. Terrel, Stepán Roucka, Ashutosh Saboo, Isuru Fernando, Sumith Kulal, Robert Cimrman, Anthony M. Scopatz
SymPy: symbolic computing in Python. PeerJ Comput. Sci. 3 (2017)
Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien
Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization. CoRR (2017)
Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien
Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization. NIPS (2017)
Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort
On the Consistency of Ordinal Regression Methods. J. Mach. Learn. Res. 18 (2017)
Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
ASAGA: Asynchronous Parallel SAGA. AISTATS (2017)
Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
Asaga: Asynchronous Parallel Saga. CoRR (2016)
Aaron Meurer, Christopher P. Smith, Mateusz Paprocki, Ondrej Certík, Matthew Rocklin, Amit Kumar, Sergiu Ivanov, Jason Keith Moore, Sartaj Singh, Thilina Rathnayake, Sean Vig, Brian E. Granger, Richard P. Muller, Francesco Bonazzi, Harsh Gupta, Shivam Vats, Fredrik Johansson, Fabian Pedregosa, Matthew J. Curry, Ashutosh Saboo, Isuru Fernando, Sumith Kulal, Robert Cimrman, Anthony M. Scopatz
SymPy: Symbolic computing in Python. PeerJ Prepr. 4 (2016)
Valentina Borghesani, Fabian Pedregosa, Marco Buiatti, Alexis Amadon, Evelyn Eger, Manuela Piazza
Word meaning in the ventral visual path: a perceptual to conceptual gradient of semantic coding. NeuroImage 143 (2016)
Fabian Pedregosa
Hyperparameter optimization with approximate gradient. CoRR (2016)
Fabian Pedregosa
Hyperparameter optimization with approximate gradient. ICML (2016)
Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Bertrand Thirion, Alexandre Gramfort
Data-driven HRF estimation for encoding and decoding models. NeuroImage 104 (2015)
Gaël Varoquaux, Lars Buitinck, Gilles Louppe, Olivier Grisel, Fabian Pedregosa, Andreas Mueller
Scikit-learn: Machine Learning Without Learning the Machinery. GetMobile Mob. Comput. Commun. 19 (1) (2015)
Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
Machine Learning for Neuroimaging with Scikit-Learn. CoRR (2014)
Valentina Borghesani, Fabian Pedregosa, Evelyn Eger, Marco Buiatti, Manuela Piazza
A perceptual-to-conceptual gradient of word coding along the ventral path. PRNI (2014)
Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort
On the Consistency of Ordinal Regression Methods. CoRR (2014)
Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Alexandre Gramfort, Bertrand Thirion
Data-driven HRF estimation for encoding and decoding models. CoRR (2014)
Yousra Bekhti, Nicolas Zilber, Fabian Pedregosa, Philippe Ciuciu, Virginie van Wassenhove, Alexandre Gramfort
Decoding perceptual thresholds from MEG/EEG. PRNI (2014)
Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
Machine learning for neuroimaging with scikit-learn. Frontiers Neuroinformatics 8 (2014)
Fernando Yepes-Calderon, Fabian Pedregosa, Bertrand Thirion, Yalin Wang, Natasha Leporé
Automatic pathology classification using a single feature machine learning support - vector machines. Medical Imaging: Computer-Aided Diagnosis (2014)
Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, Robert Layton, Jake VanderPlas, Arnaud Joly, Brian Holt, Gaël Varoquaux
API design for machine learning software: experiences from the scikit-learn project. CoRR (2013)
Michael Eickenberg, Fabian Pedregosa, Senoussi Mehdi, Alexandre Gramfort, Bertrand Thirion
Second order scattering descriptors predict fMRI activity due to visual textures. CoRR (2013)
Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort
HRF Estimation Improves Sensitivity of fMRI Encoding and Decoding Models. PRNI (2013)
Michael Eickenberg, Mehdi Senoussi, Fabian Pedregosa, Alexandre Gramfort, Bertrand Thirion
Second Order Scattering Descriptors Predict fMRI Activity Due to Visual Textures. PRNI (2013)
Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort
HRF estimation improves sensitivity of fMRI encoding and decoding models CoRR (2013)
Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion, Christophe Pallier, Elodie Cauvet
Improved brain pattern recovery through ranking approaches CoRR (2012)
Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Elodie Cauvet, Christophe Pallier, Bertrand Thirion
Learning to rank from medical imaging data CoRR (2012)
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake VanderPlas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Edouard Duchesnay
Scikit-learn: Machine Learning in Python CoRR (2012)
Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux, Christophe Pallier, Bertrand Thirion, Alexandre Gramfort
Improved Brain Pattern Recovery through Ranking Approaches. PRNI (2012)
Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux, Christophe Pallier, Bertrand Thirion, Alexandre Gramfort
Learning to Rank from Medical Imaging Data. MLMI (2012)
Gaël Varoquaux, Alexandre Gramfort, Fabian Pedregosa, Vincent Michel, Bertrand Thirion
Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity. IPMI (2011)
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake VanderPlas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Edouard Duchesnay
Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 12 (2011)