Fabian Pedregosa

86 papers A* 16A 7Journal 54Unranked 9

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	How far away are truly hyperparameter-free learning algorithms? CoRR Priya Kasimbeg, Vincent Roulet, Naman Agarwal, Sourabh Medapati, Fabian Pedregosa, Atish Agarwala, George E. Dahl
2025	J	`jnl`	How far away are truly hyperparameter-free learning algorithms? Trans. Mach. Learn. Res. Priya Kasimbeg, Vincent Roulet, Naman Agarwal, Sourabh Medapati, Fabian Pedregosa, Atish Agarwala, George E. Dahl
2025	J	`jnl`	Stability-Aware Training of Machine Learning Force Fields with Differentiable Boltzmann Estimators. Trans. Mach. Learn. Res. Sanjeev Raja, Ishan Amin, Fabian Pedregosa, Aditi S. Krishnapriyan
2024	J	`jnl`	Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition. CoRR 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
2024	J	`jnl`	Stability-Aware Training of Neural Network Interatomic Potentials with Differentiable Boltzmann Estimators. CoRR Sanjeev Raja, Ishan Amin, Fabian Pedregosa, Aditi S. Krishnapriyan
2024	A*	`conf`	Stepping on the Edge: Curvature Aware Learning Rate Tuners. NeurIPS Vincent Roulet, Atish Agarwala, Jean-Bastien Grill, Grzegorz Swirszcz, Mathieu Blondel, Fabian Pedregosa
2024	J	`jnl`	Stepping on the Edge: Curvature Aware Learning Rate Tuners. CoRR Vincent Roulet, Atish Agarwala, Jean-Bastien Grill, Grzegorz Swirszcz, Mathieu Blondel, Fabian Pedregosa
2024	J	`jnl`	Unlearning in- vs. out-of-distribution data in LLMs under gradient-based method. CoRR Teodora Baluta, Pascal Lamblin, Daniel Tarlow, Fabian Pedregosa, Gintare Karolina Dziugaite
2024	J	`jnl`	When is Momentum Extragradient Optimal? A Polynomial-Based Analysis. Trans. Mach. Learn. Res. Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
2023	A	`conf`	A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. AISTATS Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2023	J	`jnl`	Halting Time is Predictable for Large Models: A Universality Property and Average-Case Analysis. Found. Comput. Math. Courtney Paquette, Bart van Merriënboer, Elliot Paquette, Fabian Pedregosa
2023	J	`jnl`	On the Interplay Between Stepsize Tuning and Progressive Sharpening. CoRR Vincent Roulet, Atish Agarwala, Fabian Pedregosa
2023	A*	`conf`	Second-order regression models exhibit progressive sharpening to the edge of stability. ICML Atish Agarwala, Fabian Pedregosa, Jeffrey Pennington
2022	J	`jnl`	A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces. CoRR Charline Le Lan, Joshua Greaves, Jesse Farebrother, Mark Rowland, Fabian Pedregosa, Rishabh Agarwal, Marc G. Bellemare
2022	J	`jnl`	Cutting Some Slack for SGD with Adaptive Polyak Stepsizes. CoRR Robert M. Gower, Mathieu Blondel, Nidham Gazagnadou, Fabian Pedregosa
2022	A*	`conf`	Efficient and Modular Implicit Differentiation. NeurIPS Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
2022	J	`jnl`	Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum. CoRR Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
2022	A*	`conf`	GradMax: Growing Neural Networks using Gradient Information. ICLR Utku Evci, Bart van Merrienboer, Thomas Unterthiner, Fabian Pedregosa, Max Vladymyrov
2022	J	`jnl`	GradMax: Growing Neural Networks using Gradient Information. CoRR Utku Evci, Max Vladymyrov, Thomas Unterthiner, Bart van Merriënboer, Fabian Pedregosa
2022	A*	`conf`	On Implicit Bias in Overparameterized Bilevel Optimization. ICML Paul Vicol, Jonathan P. Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse
2022	J	`jnl`	On Implicit Bias in Overparameterized Bilevel Optimization. CoRR Paul Vicol, Jonathan Lorraine, Fabian Pedregosa, David Duvenaud, Roger B. Grosse
2022	J	`jnl`	Only Tails Matter: Average-Case Universality and Robustness in the Convex Regime. CoRR Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
2022	A*	`conf`	Only tails matter: Average-Case Universality and Robustness in the Convex Regime. ICML Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
2022	J	`jnl`	Second-order regression models exhibit progressive sharpening to the edge of stability. CoRR Atish Agarwala, Fabian Pedregosa, Jeffrey Pennington
2022	A	`conf`	Super-Acceleration with Cyclical Step-sizes. AISTATS Baptiste Goujaud, Damien Scieur, Aymeric Dieuleveut, Adrien B. Taylor, Fabian Pedregosa
2022	A*	`conf`	The Curse of Unrolling: Rate of Differentiating Through Optimization. NeurIPS Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa
2021	A*	`conf`	Average-case Acceleration for Bilinear Games and Normal Matrices. ICLR Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur
2021	A*	`conf`	Boosting Variational Inference With Locally Adaptive Step-Sizes. IJCAI Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
2021	J	`jnl`	Boosting Variational Inference With Locally Adaptive Step-Sizes. CoRR Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
2021	J	`jnl`	Bridging the Gap Between Adversarial Robustness and Optimization Bias. CoRR Fartash Faghri, Cristina Nader Vasconcelos, David J. Fleet, Fabian Pedregosa, Nicolas Le Roux
2021	J	`jnl`	Efficient and Modular Implicit Differentiation. CoRR Mathieu Blondel, Quentin Berthet, Marco Cuturi, Roy Frostig, Stephan Hoyer, Felipe Llinares-López, Fabian Pedregosa, Jean-Philippe Vert
2021	A*	`conf`	SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality. COLT Courtney Paquette, Kiwon Lee, Fabian Pedregosa, Elliot Paquette
2021	J	`jnl`	SGD in the Large: Average-case Analysis, Asymptotics, and Stepsize Criticality. CoRR Courtney Paquette, Kiwon Lee, Fabian Pedregosa, Elliot Paquette
2020	A*	`conf`	Acceleration through spectral density estimation. ICML Fabian Pedregosa, Damien Scieur
2020	J	`jnl`	Average-case Acceleration Through Spectral Density Estimation. CoRR Fabian Pedregosa, Damien Scieur
2020	J	`jnl`	Average-case Acceleration for Bilinear Games and Normal Matrices. CoRR Carles Domingo-Enrich, Fabian Pedregosa, Damien Scieur
2020	A	`conf`	Linearly Convergent Frank-Wolfe without Line-Search. AISTATS Fabian Pedregosa, Geoffrey Négiar, Armin Askari, Martin Jaggi
2020	A	`conf`	On the interplay between noise and curvature and its effect on optimization and generalization. AISTATS Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux
2020	A*	`conf`	Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. ICML Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Robert Freund, Fabian Pedregosa
2020	J	`jnl`	Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization. CoRR Geoffrey Négiar, Gideon Dresdner, Alicia Y. Tsai, Laurent El Ghaoui, Francesco Locatello, Fabian Pedregosa
2020	J	`jnl`	The Geometry of Sign Gradient Descent. CoRR Lukas Balles, Fabian Pedregosa, Nicolas Le Roux
2020	A*	`conf`	Universal Asymptotic Optimality of Polyak Momentum. ICML Damien Scieur, Fabian Pedregosa
2019	J	`jnl`	A Test for Shared Patterns in Cross-modal Brain Activation Analysis. CoRR Elena Kalinina, Fabian Pedregosa, Vittorio Iacovella, Emanuele Olivetti, Paolo Avesani
2019	J	`jnl`	Information matrices and generalization. CoRR Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio, Nicolas Le Roux
2019	A	`conf`	Proximal Splitting Meets Variance Reduction. AISTATS Fabian Pedregosa, Kilian Fatras, Mattia Casotto
2019	J	`jnl`	SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python. CoRR 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, CJ 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
2019	J	`jnl`	The Difficulty of Training Sparse Neural Networks. CoRR Utku Evci, Fabian Pedregosa, Aidan N. Gomez, Erich Elsen
2018	A*	`conf`	Adaptive Three Operator Splitting. ICML Fabian Pedregosa, Gauthier Gidel
2018	J	`jnl`	Adaptive Three Operator Splitting. CoRR Fabian Pedregosa, Gauthier Gidel
2018	A	`conf`	Frank-Wolfe Splitting via Augmented Lagrangian Method. AISTATS Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Frank-Wolfe Splitting via Augmented Lagrangian Method. CoRR Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
2018	A*	`conf`	Frank-Wolfe with Subsampling Oracle. ICML Thomas Kerdreux, Fabian Pedregosa, Alexandre d'Aspremont
2018	J	`jnl`	Frank-Wolfe with Subsampling Oracle. CoRR Thomas Kerdreux, Fabian Pedregosa, Alexandre d'Aspremont
2018	J	`jnl`	Improved Asynchronous Parallel Optimization Analysis for Stochastic Incremental Methods. J. Mach. Learn. Res. Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Improved asynchronous parallel optimization analysis for stochastic incremental methods. CoRR Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2017	A	`conf`	ASAGA: Asynchronous Parallel SAGA. AISTATS Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2017	—	`conf`	Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization. NIPS Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien
2017	J	`jnl`	Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization. CoRR Fabian Pedregosa, Rémi Leblond, Simon Lacoste-Julien
2017	J	`jnl`	On the Consistency of Ordinal Regression Methods. J. Mach. Learn. Res. Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort
2017	J	`jnl`	SymPy: symbolic computing in Python. PeerJ Comput. Sci. 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
2016	J	`jnl`	Asaga: Asynchronous Parallel Saga. CoRR Rémi Leblond, Fabian Pedregosa, Simon Lacoste-Julien
2016	A*	`conf`	Hyperparameter optimization with approximate gradient. ICML Fabian Pedregosa
2016	J	`jnl`	Hyperparameter optimization with approximate gradient. CoRR Fabian Pedregosa
2016	J	`jnl`	SymPy: Symbolic computing in Python. PeerJ Prepr. 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
2016	J	`jnl`	Word meaning in the ventral visual path: a perceptual to conceptual gradient of semantic coding. NeuroImage Valentina Borghesani, Fabian Pedregosa, Marco Buiatti, Alexis Amadon, Evelyn Eger, Manuela Piazza
2015	J	`jnl`	Data-driven HRF estimation for encoding and decoding models. NeuroImage Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Bertrand Thirion, Alexandre Gramfort
2015	J	`jnl`	Scikit-learn: Machine Learning Without Learning the Machinery. GetMobile Mob. Comput. Commun. Gaël Varoquaux, Lars Buitinck, Gilles Louppe, Olivier Grisel, Fabian Pedregosa, Andreas Mueller
2014	—	`conf`	A perceptual-to-conceptual gradient of word coding along the ventral path. PRNI Valentina Borghesani, Fabian Pedregosa, Evelyn Eger, Marco Buiatti, Manuela Piazza
2014	—	`conf`	Automatic pathology classification using a single feature machine learning support - vector machines. Computer-Aided Diagnosis Fernando Yepes-Calderon, Fabian Pedregosa, Bertrand Thirion, Yalin Wang, Natasha Leporé
2014	J	`jnl`	Data-driven HRF estimation for encoding and decoding models. CoRR Fabian Pedregosa, Michael Eickenberg, Philippe Ciuciu, Alexandre Gramfort, Bertrand Thirion
2014	—	`conf`	Decoding perceptual thresholds from MEG/EEG. PRNI Yousra Bekhti, Nicolas Zilber, Fabian Pedregosa, Philippe Ciuciu, Virginie van Wassenhove, Alexandre Gramfort
2014	J	`jnl`	Machine Learning for Neuroimaging with Scikit-Learn. CoRR Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
2014	J	`jnl`	Machine learning for neuroimaging with scikit-learn. Frontiers Neuroinformatics Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg, Philippe Gervais, Andreas Mueller, Jean Kossaifi, Alexandre Gramfort, Bertrand Thirion, Gaël Varoquaux
2014	J	`jnl`	On the Consistency of Ordinal Regression Methods. CoRR Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort
2013	J	`jnl`	API design for machine learning software: experiences from the scikit-learn project. CoRR 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
2013	—	`conf`	HRF Estimation Improves Sensitivity of fMRI Encoding and Decoding Models. PRNI Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort
2013	J	`jnl`	HRF estimation improves sensitivity of fMRI encoding and decoding models CoRR Fabian Pedregosa, Michael Eickenberg, Bertrand Thirion, Alexandre Gramfort
2013	—	`conf`	Second Order Scattering Descriptors Predict fMRI Activity Due to Visual Textures. PRNI Michael Eickenberg, Mehdi Senoussi, Fabian Pedregosa, Alexandre Gramfort, Bertrand Thirion
2013	J	`jnl`	Second order scattering descriptors predict fMRI activity due to visual textures. CoRR Michael Eickenberg, Fabian Pedregosa, Senoussi Mehdi, Alexandre Gramfort, Bertrand Thirion
2012	—	`conf`	Improved Brain Pattern Recovery through Ranking Approaches. PRNI Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux, Christophe Pallier, Bertrand Thirion, Alexandre Gramfort
2012	J	`jnl`	Improved brain pattern recovery through ranking approaches CoRR Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Bertrand Thirion, Christophe Pallier, Elodie Cauvet
2012	—	`conf`	Learning to Rank from Medical Imaging Data. MLMI Fabian Pedregosa, Elodie Cauvet, Gaël Varoquaux, Christophe Pallier, Bertrand Thirion, Alexandre Gramfort
2012	J	`jnl`	Learning to rank from medical imaging data CoRR Fabian Pedregosa, Alexandre Gramfort, Gaël Varoquaux, Elodie Cauvet, Christophe Pallier, Bertrand Thirion
2012	J	`jnl`	Scikit-learn: Machine Learning in Python CoRR 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
2011	—	`conf`	Multi-subject Dictionary Learning to Segment an Atlas of Brain Spontaneous Activity. IPMI Gaël Varoquaux, Alexandre Gramfort, Fabian Pedregosa, Vincent Michel, Bertrand Thirion
2011	J	`jnl`	Scikit-learn: Machine Learning in Python. J. Mach. Learn. Res. 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