Publications related to Clebsch Optimal Control Formulation In Mechanics

Spectral Estimators for High-Dimensional Matrix Inference

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Optimal denoising of rotationally invariant rectangular matrices

Florent Gérard Krzakala, Lenka Zdeborová, Emanuele Troiani, Vittorio Erba

In this manuscript we consider denoising of large rectangular matrices: given a noisy observation of a signal matrix, what is the best way of recovering the signal matrix itself? For Gaussian noise and rotationally-invariant signal priors, we completely ch ...

2022

Fast deterministic and randomized algorithms for low-rank approximation, matrix functions, and trace estimation

Alice Cortinovis

In this thesis we propose and analyze algorithms for some numerical linear algebra tasks: finding low-rank approximations of matrices, computing matrix functions, and estimating the trace of matrices.In the first part, we consider algorithms for building l ...

EPFL2022

Robust Differentiable SVD

Pascal Fua, Mathieu Salzmann, Zheng Dang, Wei Wang, Yinlin Hu

Eigendecomposition of symmetric matrices is at the heart of many computer vision algorithms. However, the derivatives of the eigenvectors tend to be numerically unstable, whether using the SVD to compute them analytically or using the Power Iteration (PI) ...

2021

A new regret analysis for Adam-type algorithms

Volkan Cevher, Ahmet Alacaoglu

In this paper, we focus on a theory-practice gap for Adam and its variants (AMSgrad, AdamNC, etc.). In practice, these algorithms are used with a constant first-order moment parameter 1 (typically between 0:9 and 0:99). In theory, regret guarantees for onl ...

2020

Unified Approach to Convex Robust Distributed Control Given Arbitrary Information Structures

Maryam Kamgarpour, Luca Furieri

We consider the problem of computing optimal linear control policies for linear systems in finite-horizon. The states and the inputs are required to remain inside prespecified safety sets at all times despite unknown disturbances. In this technical note, w ...

2019

Kernel methods and Model predictive approaches for Learning and Control

Sanket Sanjay Diwale

Data-driven modeling and feedback control play a vital role in several application areas ranging from robotics, control theory, manufacturing to management of assets, financial portfolios and supply chains. Many such problems in one way or another are rela ...

EPFL2019

Second-order sensitivity in the cylinder wake: Optimal spanwise-periodic wall actuation and wall deformation

François Gallaire, Edouard Boujo, Andrea Fani

Two-dimensional (2D) flows can be controlled efficiently using spanwise "waviness," i.e., a control (e.g., wall blowing and suction or wall deformation) that is periodic in the spanwise direction. This study tackles the global linear stability of 2D flows ...

AMER PHYSICAL SOC2019

A priori error for unilateral contact problems with Lagrange multipliers and isogeometric analysis

Annalisa Buffa, Pablo Antolin Sanchez, Mathieu Jonathan Fabre

In this paper, we consider unilateral contact problem without friction between a rigid body and deformable one in the framework of isogeometric analysis. We present the theoretical analysis of the mixed problem. For the displacement, we use the pushforward ...

2019

Jordan blocks of unipotent elements in some irreducible representations of classical groups in good characteristic

Mikko Tapani Korhonen

Let

G

be a classical group with natural module

V

over an algebraically closed field of good characteristic. For every unipotent element

u

of

G

, we describe the Jordan block sizes of

u

on the irreducible

G

-modules which occur as compositio ...

2019

Clebsch Optimal Control Formulation In Mechanics

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Spectral Estimators for High-Dimensional Matrix Inference

Optimal denoising of rotationally invariant rectangular matrices

Fast deterministic and randomized algorithms for low-rank approximation, matrix functions, and trace estimation

Robust Differentiable SVD

A new regret analysis for Adam-type algorithms

Unified Approach to Convex Robust Distributed Control Given Arbitrary Information Structures

Kernel methods and Model predictive approaches for Learning and Control

Second-order sensitivity in the cylinder wake: Optimal spanwise-periodic wall actuation and wall deformation

A priori error for unilateral contact problems with Lagrange multipliers and isogeometric analysis

Jordan blocks of unipotent elements in some irreducible representations of classical groups in good characteristic

Optimal denoising of rotationally invariant rectangular matrices

Robust Differentiable SVD

Spectral Estimators for High-Dimensional Matrix Inference

Unified Approach to Convex Robust Distributed Control Given Arbitrary Information Structures

Fast deterministic and randomized algorithms for low-rank approximation, matrix functions, and trace estimation

Kernel methods and Model predictive approaches for Learning and Control

Jordan blocks of unipotent elements in some irreducible representations of classical groups in good characteristic

A priori error for unilateral contact problems with Lagrange multipliers and isogeometric analysis

A new regret analysis for Adam-type algorithms

Second-order sensitivity in the cylinder wake: Optimal spanwise-periodic wall actuation and wall deformation