From the 1 of 15 linked papers with an AI index.
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Proximal basin hopping: global optimization with guarantees
Guillaume Lauga, Cesare Molinari, Samuel Vaiter
Global optimization is a challenging problem, with plenty of algorithms displaying empirical success, but scarce theoretical backing. In this work, we propose a new theoretical fra…
SGD for Variational Inference: Tackling Unbounded Variance via Preconditioning and Dynamic Batching
Hippolyte Labarrière, Cesare Molinari, Silvia Villa +1
Black-Box Variational Inference (BBVI) typically relies on Stochastic Gradient Descent (SGD) to optimize the Evidence Lower Bound (ELBO). However, the stochastic gradients in BBVI…
Optimization Insights into Deep Diagonal Linear Networks
Hippolyte Labarrière, Cesare Molinari, Lorenzo Rosasco +2
Gradient-based methods successfully train highly overparameterized models in practice, even though the associated optimization problems are markedly nonconvex. Understanding the me…