4 papers · 1 filter
Accelerated Stochastic Zeroth-Order Quasar-Convex Optimization
Eméric Gbaguidi, Julien Hermant
We consider unconstrained minimization of smooth quasar-convex functions when only noisy function evaluations are accessible through a stochastic zeroth-order oracle. For these non…
Acceleration for Polyak-Łojasiewicz Functions with a Gradient Aiming Condition
Julien Hermant
It is known that when minimizing smooth Polyak-Łojasiewicz (PL) functions, momentum algorithms cannot significantly improve the convergence bound of gradient descent, contrasting w…
Continuized Nesterov Momentum Achieves the Complexity in Smooth Nonconvex Optimization
Julien Hermant, Jean-François Aujol, Charles Dossal +3
For first-order optimization of non-convex functions with Lipschitz-continuous gradient and Hessian, the best-known complexity for reaching an -approximation of a stat…
Continuized Nesterov Acceleration for Non-Convex Optimization
Julien Hermant, Jean-François Aujol, Charles Dossal +2
In convex optimization, continuous-time counterparts have been a fruitful tool for analyzing momentum algorithms. Fewer such examples are available when the function to minimize is…