Convergence of constant step stochastic gradient descent for non-smooth non-convex functions. - Pascal Bianchi; Walid Hachem; Sholom Schechtman (CoRR, 2020)

ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks. - Louis Leconte; Sholom Schechtman; Eric Moulines (AISTATS, 2023)

Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold. - Sholom Schechtman; Daniil Tiapkin; Michael Muehlebach; Éric Moulines (COLT, 2023)

Stochastic proximal subgradient descent oscillates in the vicinity of its accumulation set. - Sholom Schechtman (Optim. Lett., 2023)

Stochastic Subgradient Descent Escapes Active Strict Saddles on Weakly Convex Functions. - Pascal Bianchi; Walid Hachem; Sholom Schechtman (Math. Oper. Res., 2024)

The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks. - Sholom Schechtman; Nicolas Schreuder (COLT, 2025)