98 citations · 154 across the 15 of their papers we have counts for
5 papers · 1 filter
Convergence Analysis of Homotopy-SGD for non-convex optimization
Matilde Gargiani, Andrea Zanelli, Quoc Tran-Dinh +2
First-order stochastic methods for solving large-scale non-convex optimization problems are widely used in many big-data applications, e.g. training deep neural networks as well as…
An Efficient Real-Time NMPC for Quadrotor Position Control under Communication Time-Delay
Barbara Barros Carlos, Tommaso Sartor, Andrea Zanelli +4
The advances in computer processor technology have enabled the application of nonlinear model predictive control (NMPC) to agile systems, such as quadrotors. These systems are char…
On the Promise of the Stochastic Generalized Gauss-Newton Method for Training DNNs
Matilde Gargiani, Andrea Zanelli, Moritz Diehl +1
Following early work on Hessian-free methods for deep learning, we study a stochastic generalized Gauss-Newton method (SGN) for training DNNs. SGN is a second-order optimization me…
A Lyapunov Function for the Combined System-Optimizer Dynamics in Inexact Model Predictive Control
Andrea Zanelli, Quoc Tran Dinh, Moritz Diehl
In this paper, an asymptotic stability proof for a class of methods for inexact nonlinear model predictive control is presented. General Q-linearly convergent online optimization m…
CIAO: MPC-based Safe Motion Planning in Predictable Dynamic Environments
Tobias Schoels, Per Rutquist, Luigi Palmieri +3
Robots have been operating in dynamic environments and shared workspaces for decades. Most optimization based motion planning methods, however, do not consider the movement of othe…