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A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Laboratoire d'automatique 1

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The role of PDE-based parameterization techniques in gradient-based IGA shape optimization applications

Stabilization and Accuracy Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method

Efficient Learning of a Linear Dynamical System with Stability Guarantees

Probabilistic Adaptive Control for Robust Behavior Imitation

Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

Whole Body Model Predictive Control with a Memory of Motion:Experiments on a Torque-Controlled Talos

Optimal Thrust Vector Control of an Electric Small-Scale Rocket Prototype

A first-order primal-dual method with adaptivity to local smoothness