Patrimony

The Louis Bachelier Group's patrimony has been defined as all the publications produced by academic researchers thanks to Group funding (ILB, FdR, IEF, Labex) or via the use of EquipEx data (BEDOFIH, EUROFIDAI).


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Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression.

Accelerated gra- dient, Convex optimization, Least-squares regression, Non-parametric estimation, Stochastic gradient

Stochastic approximation and least-squares regression, with applications to machine learning.

Acceleration, Accélération, Algorithme dual moyenné, Apprentissage de permutation, Approximation stochastique, Averaging, Contraintes de forme, Convex optimization, Convex relaxation, Descente miroire, Discriminative clustering, Dual averaging, Estimation minimax, Gradient stochastique, Least-squares regression, Minimax estimation, Mirror descent, Moyennage, Optimisation convexe, Parcimonie, Partionnement discriminatif, Permutation learning, Relaxation convexe, Régression par moindres carrés, Shape constraints, Sparsity, Statistical seriation, Stochastic approximation, Stochastic gradient, Sériation statistique

Stochastic Composite Least-Squares Regression with Convergence Rate O(1/n).

Accelerated gra- dient, Convex optimization, Least-squares regression, Non-parametric estimation, Stochastic gradient

Stochastic approximation and least-squares regression, with applications to machine learning.

Acceleration, Algorithme dual moyenné, Apprentissage de permutation, Approximation stochastique, Averaging, Contraintes de forme, Convex optimization, Convex relaxation, Descente miroire, Discriminative clustering, Dual averaging, Estimation minimax, Gradient stochastique, Least-squares regression, Minimax estimation, Mirror descent, Moyennage, Optimisation convexe, Parcimonie, Partionnement discriminatif, Permutation learning, Relaxation convexe, Régression par moindres carrés, Shape constraints, Sparsity, Statistical seriation, Stochastic approximation, Stochastic gradient, Sériation statistique