From the 1 of 123 linked papers with an AI index.
735 citations · 3k across the 69 of their papers we have counts for
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Structure-Adaptive, Variance-Reduced, and Accelerated Stochastic Optimization
Junqi Tang, Francis Bach, Mohammad Golbabaee +1
In this work we explore the fundamental structure-adaptiveness of state of the art randomized first order algorithms on regularized empirical risk minimization tasks, where the sol…
AdaBatch: Efficient Gradient Aggregation Rules for Sequential and Parallel Stochastic Gradient Methods
Alexandre Défossez, Francis Bach
We study a new aggregation operator for gradients coming from a mini-batch for stochastic gradient (SG) methods that allows a significant speed-up in the case of sparse optimizatio…
Convex optimization over intersection of simple sets: improved convergence rate guarantees via an exact penalty approach
Achintya Kundu, Francis Bach, Chiranjib Bhattacharyya
We consider the problem of minimizing a convex function over the intersection of finitely many simple sets which are easy to project onto. This is an important problem arising in v…
A Generic Approach for Escaping Saddle points
Sashank J Reddi, Manzil Zaheer, Suvrit Sra +4
A central challenge to using first-order methods for optimizing nonconvex problems is the presence of saddle points. First-order methods often get stuck at saddle points, greatly d…
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization
Francis Bach
We consider the minimization of submodular functions subject to ordering constraints. We show that this optimization problem can be cast as a convex optimization problem on a space…
Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance
Jonathan Weed, Francis Bach
The Wasserstein distance between two probability measures on a metric space is a measure of closeness with applications in statistics, probability, and machine learning. In this wo…