Concept
Inégalité de Jensen
Publications associées (20)
WILD SOLUTIONS TO SCALAR EULER-LAGRANGE EQUATIONS
. We study very weak solutions to scalar Euler-Lagrange equations associated with quadratic convex functionals. We investigate whether W1,1 solutions are necessarily W 1,2 Nash and Schauder applicable. We answer this question positively for a suitable clas ...
Amer Mathematical Soc2024Incentive Mechanism in the Sponsored Content Market With Network Effects
We propose an incentive mechanism for the sponsored content provider (CP) market in which the communication of users can be represented by a graph, and the private information of the users is assumed to have a continuous distribution function. The CP stipu ...
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023Universal and adaptive methods for robust stochastic optimization
Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...
EPFL2023Forward-reflected-backward method with variance reduction
Volkan Cevher, Ahmet Alacaoglu
We propose a variance reduced algorithm for solving monotone variational inequalities. Without assuming strong monotonicity, cocoercivity, or boundedness of the domain, we prove almost sure convergence of the iterates generated by the algorithm to a soluti ...
2021Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates
Martin Jaggi, Sebastian Urban Stich, Amirkeivan Mohtashami
It has been experimentally observed that the efficiency of distributed training with stochastic gradient (SGD) depends decisively on the batch size and—in asynchronous implementations—on the gradient staleness. Especially, it has been observed that the spe ...
2021Random extrapolation for primal-dual coordinate descent
Volkan Cevher, Ahmet Alacaoglu
We introduce a randomly extrapolated primal-dual coordinate descent method that adapts to sparsity of the data matrix and the favorable structures of the objective function. Our method updates only a subset of primal and dual variables with sparse data, an ...
2020