Publications related to On the selection of optimal nonlinearities for stochastic gradient adaptive algorithms

Investigation of Self-Sensing Techniques for Dielectric Elastomer Actuators

Self-sensing allows to use a Dielectric Elastomer Actuator (DEA) simultaneously as an actuator and sensor, without the need of external sensors. DEAs are composed of a dielectric elastomer that is sandwiched between two electrodes. If a voltage difference ...

2023

Distributionally Robust Linear Quadratic Control

Daniel Kuhn, Bahar Taskesen, Cagil Kocyigit

Linear-Quadratic-Gaussian (LQG) control is a fundamental control paradigm that is studied in various fields such as engineering, computer science, economics, and neuroscience. It involves controlling a system with linear dynamics and imperfect observations ...

2023

Memory of Motion for Initializing Optimization in Robotics

Teguh Santoso Lembono

Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...

EPFL2022

The Gaussian lossy Gray-Wyner network

Michael Christoph Gastpar, Erixhen Sula

We consider the problem of source coding subject to a fidelity criterion for the Gray-Wyner network that connects a single source with two receivers via a common channel and two private channels. The pareto-optimal trade-offs between the sum-rate of the pr ...

2020

MATHICSE Technical Report : Ensemble Kalman filter for multiscale inverse problems

Assyr Abdulle, Giacomo Garegnani, Andrea Zanoni

We present a novel algorithm based on the ensemble Kalman filter to solve inverse problems involving multiscale elliptic partial differential equations. Our method is based on numerical homogenization and finite element discretization and allows to recover ...

MATHICSE2019

Calibration Aspects of INS Navigation

Philipp Clausen

The use of a Bayesian filter (e.g., Kalman filter) for the fusion of information from satellite positioning and inertial navigation is a common approach in many applications, where the knowledge of position, velocity, and attitude in space are of great int ...

EPFL2019

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

Volkan Cevher, Junhong Lin

We investigate regularized algorithms combining with projection for least-squares regression problem over a Hilbert space, covering nonparametric regression over a reproducing kernel Hilbert space. We prove convergence results with respect to variants of n ...

ICML2018

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

Kamiar Aminian, Arnaud Barré

The aim of this study was to analyze the accuracy of bone pose estimation based on sub-clusters of three skin-markers characterized by triangular Cosserat point elements (TCPEs) and to evaluate the capability of four instantaneous physical parameters, whic ...

Elsevier2017

Calibration of optical tweezers with non-spherical probes via high-resolution detection of Brownian motion

László Forró, Richard Gaal, Flavio Maurizio Mor, Sylvia Jeney

Optical tweezers are commonly used and powerful tools to perform force measurements on the piconewton scale and to detect nanometer-scaled displacements. However, the precision of these instruments relies to a great extent on the accuracy of the calibratio ...

Elsevier Science Bv2015

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

In this paper, we prove a new identity for the least-square solution of an over-determined set of linear equation

Ax=b

, where

A

is an

m\times n

full-rank matrix,

b

is a column-vector of dimension

m

, and

m

(the number of equations) is larger tha ...

2015

On the selection of optimal nonlinearities for stochastic gradient adaptive algorithms

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Investigation of Self-Sensing Techniques for Dielectric Elastomer Actuators

Distributionally Robust Linear Quadratic Control

Memory of Motion for Initializing Optimization in Robotics

The Gaussian lossy Gray-Wyner network

MATHICSE Technical Report : Ensemble Kalman filter for multiscale inverse problems

Calibration Aspects of INS Navigation

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

Calibration of optical tweezers with non-spherical probes via high-resolution detection of Brownian motion

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

Memory of Motion for Initializing Optimization in Robotics

Distributionally Robust Linear Quadratic Control

Calibration Aspects of INS Navigation

Investigation of Self-Sensing Techniques for Dielectric Elastomer Actuators

Calibration of optical tweezers with non-spherical probes via high-resolution detection of Brownian motion

Bone orientation and position estimation errors using Cosserat point elements and least squares methods: Application to gait

The Gaussian lossy Gray-Wyner network

A New Identity for the Least-square Solution of Overdetermined Set of Linear Equations

MATHICSE Technical Report : Ensemble Kalman filter for multiscale inverse problems

Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces