3 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
Piecewise Polynomial Regression of Tame Functions via Integer Programming
Gilles Bareilles, Johannes Aspman, Jiri Nemecek +1
Tame functions are a class of nonsmooth, nonconvex functions, which feature in a wide range of applications: functions encountered in the training of deep neural networks with all…
Hybrid Methods in Polynomial Optimisation
Johannes Aspman, Gilles Bareilles, Vyacheslav Kungurtsev +2
The Moment/Sum-of-squares hierarchy provides a way to compute the global minimizers of polynomial optimization problems (POP), at the cost of solving a sequence of increasingly lar…
Tame Riemannian Stochastic Approximation
Johannes Aspman, Vyacheslav Kungurtsev, Reza Roohi Seraji
We study the properties of stochastic approximation applied to a tame nondifferentiable function subject to constraints defined by a Riemannian manifold. The objective landscape of…