Francis Rene Bach
Affiliations: | École normale supérieure Paris, Paris, Île-de-France, France |
Area:
machine learningGoogle:
"Francis Bach"Mean distance: 14.44 (cluster 29) | S | N | B | C | P |
Parents
Sign in to add mentorMichael I. Jordan | grad student | 2005 | UC Berkeley | |
(Learning blind source separation.) |
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Publications
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Dieuleveut A, Durmus A, Bach F. (2020) Bridging the gap between constant step size stochastic gradient descent and Markov chains Annals of Statistics. 48: 1348-1382 |
Gower RM, Richtárik P, Bach F. (2020) Stochastic quasi-gradient methods: variance reduction via Jacobian sketching Mathematical Programming. 1-58 |
Rencker L, Bach F, Wang W, et al. (2019) Sparse Recovery and Dictionary Learning From Nonlinear Compressive Measurements Ieee Transactions On Signal Processing. 67: 5659-5670 |
Bach FR. (2019) Submodular Functions: from Discrete to Continous Domains Mathematical Programming. 175: 419-459 |
Babichev D, Bach F. (2018) Slice inverse regression with score functions Electronic Journal of Statistics. 12: 1507-1543 |
Scieur D, d’Aspremont A, Bach F. (2018) Regularized nonlinear acceleration Mathematical Programming. 179: 47-83 |
Dieuleveut A, Bach F. (2016) Nonparametric stochastic approximation with large step-sizes Annals of Statistics. 44: 1363-1399 |
Bach F, Poggio T. (2016) IntroductionSpecial issue: Deep learning Information and Inference. 5: 103-104 |
Fogel F, Jenatton R, Bach F, et al. (2015) Convex relaxations for permutation problems Siam Journal On Matrix Analysis and Applications. 36: 1465-1488 |
Bach F. (2015) Duality between subgradient and conditional gradient methods Siam Journal On Optimization. 25: 115-129 |