Publications related to Convex computation of the region of attraction of polynomial control systems

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

EPFL2023

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Michel Bierlaire

In this paper, we present a spatial branch and bound algorithm to tackle the continuous pricing problem, where demand is captured by an advanced discrete choice model (DCM). Advanced DCMs, like mixed logit or latent class models, are capable of modeling de ...

2023

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

Giancarlo Ferrari Trecate, Luca Furieri, Clara Lucía Galimberti

We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...

IEEE2022

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

Volkan Cevher, Ahmet Alacaoglu

In this paper, we analyze the recently proposed stochastic primal-dual hybrid gradient (SPDHG) algorithm and provide new theoretical results. In particular, we prove almost sure convergence of the iterates to a solution with convexity and linear convergenc ...

SIAM PUBLICATIONS2022

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

Dynamic lane restrictions on congested arterials

Nikolaos Geroliminis, Paul Richard Anderson

Buses operating in mixed traffic experience problems with delay and travel time variability in peak periods. Numerous transit priority measures are found in the literature but most rely on separating buses from other vehicles. Complete separation such as d ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Stochastic Frank-Wolfe for Composite Convex Minimization

Volkan Cevher, Alp Yurtsever

A broad class of convex optimization problems can be formulated as a semidefinite program (SDP), minimization of a convex function over the positive-semidefinite cone subject to some affine constraints. The majority of classical SDP solvers are designed fo ...

2019

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

Nisheeth Vishnoi, Laura Elisa Celis, Vijay Keswani, Lingxiao Huang

Developing classification algorithms that are fair with respect to sensitive attributes of the data is an important problem due to the increased deployment of classification algorithms in societal contexts. Several recent works have focused on studying cla ...

ASSOC COMPUTING MACHINERY2019

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

Alireza Karimi, Achille Nicoletti

In this paper, a new data-driven method for designing robust controllers is proposed for systemswith sector-bounded nonlinearities and multimodel uncertainties. The results from the circle criterion are used to generate necessary and sufficient convex cons ...

WILEY2019

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

Maryam Kamgarpour, Luca Furieri

This letter proposes a novel input-output parametrization of the set of internally stabilizing output-feedback controllers for linear time invariant (LTI) systems. Our underlying idea is to directly treat the closed-loop transfer matrices from disturbances ...

2019

Convex computation of the region of attraction of polynomial control systems

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Augmented Lagrangian Methods for Provable and Scalable Machine Learning

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

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

Dynamic lane restrictions on congested arterials

Stochastic Frank-Wolfe for Composite Convex Minimization

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Dynamic lane restrictions on congested arterials

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

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

Stochastic Frank-Wolfe for Composite Convex Minimization

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient