From the 1 of 4 linked papers with an AI index.
4 papers
Piecewise smooth functions and conservative fields: calculus for nonsmooth nonconvex optimization beyond stratification
Cheik Traoré, Cheik Traoré
The paper shows that the gradient associated with locally Lipschitz, piecewise‑smooth functions forms a selection of a conservative field, linking it to the Clarke subdifferential…
The adjoint state method for parametric definable optimization without smoothness or uniqueness
Jérôme Bolte, Edouard Pauwels, Cheik Traoré
We establish that nonconvex definable parametric optimization problems with possibly nonsmooth objectives, inequality constraints, conic constraint systems, and non-unique primal a…
Bregman Stochastic Proximal Point Algorithm with Variance Reduction
Cheik Traoré, Peter Ochs
Stochastic algorithms, especially stochastic gradient descent (SGD), have proven to be the go-to methods in data science and machine learning. In recent years, the stochastic proxi…
A Structured Proximal Stochastic Variance Reduced Zeroth-order Algorithm
Marco Rando, Cheik Traoré, Cesare Molinari +2
Minimizing finite sums of functions is a central problem in optimization, arising in numerous practical applications. Such problems are commonly addressed using first-order optimiz…