Concept
Interior-point method
Related publications (197)
A Combination Technique for Optimal Control Problems Constrained by Random PDEs
We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...
2024Efficient local linearity regularization to overcome catastrophic overfitting
Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Elias Abad Rocamora
Catastrophic overfitting (CO) in single-step adversarial training (AT) results in abrupt drops in the adversarial test accuracy (even down to 0%). For models trained with multi-step AT, it has been observed that the loss function behaves locally linearly w ...
2024Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations
Giancarlo Ferrari Trecate, Maryam Kamgarpour, Yuning Jiang, Baiwei Guo
We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge is thus to generate a sequence of feasible points converging towards an optim ...
2023A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling
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 ...
2023Beyond worst-case analysis, with or without predictions
In this thesis we design online combinatorial optimization algorithms for beyond worst-case analysis settings.In the first part, we discuss the online matching problem and prove that, in the edge arrival model, no online algorithm can achieve a competitive ...
EPFL2023An Integrated Approach to Designing Robust Turbocompressors on Gas Bearings Through Surrogate Modeling and Constrained Multi-Objective Optimization
Jürg Alexander Schiffmann, Soheyl Massoudi, Cyril Picard
Designing turbocompressors is a complex and challenging task, as it involves balancing conflicting objectives such as efficiency, stability, and robustness against manufacturing deviations. This paper proposes an integrated design methodology for turbocomp ...
2023Revisiting adversarial training for the worst-performing class
Volkan Cevher, Grigorios Chrysos, Thomas Michaelsen Pethick
Despite progress in adversarial training (AT), there is a substantial gap between the topperforming and worst-performing classes in many datasets. For example, on CIFAR10, the accuracies for the best and worst classes are 74% and 23%, respectively. We argu ...
2023UNDERGRAD: A Universal Black-Box Optimization Method with Almost Dimension-Free Convergence Rate Guarantees
Volkan Cevher, Kimon Antonakopoulos
Universal methods for optimization are designed to achieve theoretically optimal convergence rates without any prior knowledge of the problem’s regularity parameters or the accurarcy of the gradient oracle employed by the optimizer. In this regard, existin ...
2022A combination technique for optimal control problems constrained by random PDEs
We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of Optimal Control Problems (OCPs) constrained by random partial differential equ ...
EPFL2022A combined Control by Interconnection—Model Predictive Control design for constrained Port-Hamiltonian systems
This paper proposes a Control by Interconnection design, for a class of constrained Port-Hamiltonian systems, which is based on an associated Model Predictive Control optimization problem. This associated optimization problem allows to consider both state ...
2022