140 citations · 159 across the 11 of their papers we have counts for
17 papers
Massively parallelizable proximal algorithms for large-scale stochastic optimal control problems
Ajay K. Sampathirao, Panagiotis Patrinos, Alberto Bemporad +1
Scenario-based stochastic optimal control problems suffer from the curse of dimensionality as they can easily grow to six and seven figure sizes. First-order methods are suitable a…
A machine-learning approach to synthesize virtual sensors for parameter-varying systems
Daniele Masti, Daniele Bernardini, Alberto Bemporad
This paper introduces a novel model-free approach to synthesize virtual sensors for the estimation of dynamical quantities that are unmeasurable at runtime but are available for de…
Piecewise linear regression and classification
Alberto Bemporad
This paper proposes a method for solving multivariate regression and classification problems using piecewise linear predictors over a polyhedral partition of the feature space. The…
A Dual Active-Set Solver for Embedded Quadratic Programming Using Recursive LDL' Updates
Daniel Arnström, Alberto Bemporad, Daniel Axehill
In this paper we present a dual active-set solver for quadratic programming which has properties suitable for use in embedded model predictive control applications. In particular,…
Exact and Heuristic Methods with Warm-start for Embedded Mixed-Integer Quadratic Programming Based on Accelerated Dual Gradient Projection
Vihangkumar V. Naik, Alberto Bemporad
Small-scale Mixed-Integer Quadratic Programming (MIQP) problems often arise in embedded control and estimation applications. Driven by the need for algorithmic simplicity to target…
Reduction of the Number of Variables in Parametric Constrained Least-Squares Problems
Alberto Bemporad, Gionata Cimini
For linearly constrained least-squares problems that depend on a vector of parameters, this paper proposes techniques for reducing the number of involved optimization variables. Af…