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Finding symmetry breaking order parameters with Euclidean neural networks

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Distributed Coupled Learning Over Adaptive Networks

Ali H. Sayed, Sulaiman A S A E Alghunaim

This work develops an effective distributed algorithm for the solution of stochastic optimization problems that involve partial coupling among both local constraints and local cost functions. While the collection of networked agents is interested in discov ...

IEEE2018

Current Trends in Multidrug Optimization: An Alley of Future Successful Treatment of Complex Disorders

Patrycja Nowak-Sliwinska

The identification of effective and long-lasting cancer therapies still remains elusive, partially due to patient and tumor heterogeneity, acquired drug resistance, and single-drug dose-limiting toxicities. The use of drug combinations may help to overcome ...

Sage Publications Inc2017

Riemannian Optimization for Solving High-Dimensional Problems with Low-Rank Tensor Structure

Michael Maximilian Steinlechner

In this thesis, we present a Riemannian framework for the solution of high-dimensional optimization problems with an underlying low-rank tensor structure. Here, the high-dimensionality refers to the size of the search space, while the cost function is scal ...

EPFL2016

Particle Swarm Optimization and Kalman Filtering for Demand Prediction of Commercial Buildings

François Maréchal, Samira Fazlollahi, Araz Ashouri

The integration of weather forecasts and demand prediction into the energy management system of buildings is usually achieved using a model-based predictive control. The performance of such control techniques strongly depends on the accuracy of the thermal ...

2015

Form-Finding Of Interlaced Space Structures

Yves Weinand, Seyed Sina Nabaei, Olivier Baverel

By Interlaced Space Structures (ISS) we mean a coupled system of naturally curved flexible panels/strips interlaced together according to a design pattern. We are looking for a physically-based and efficient form-finding procedure in order to interactively ...

Int Center Numerical Methods Engineering2014

Rotor Design Optimization for a Reaction Sphere Actuator

Yves Perriard, Leopoldo Rossini

This paper presents the rotor design optimization for a reaction sphere (RS) actuator. The RS is a permanent-magnet synchronous spherical actuator whose rotor is magnetically levitated and can be accelerated about any desired axis. The RS is composed of an ...

Institute of Electrical and Electronics Engineers2014

Form-finding Of Interlaced Space Structures

Yves Weinand, Seyed Sina Nabaei, Olivier Baverel

2014

View Selection Policy For Multi-View Video Delivery

We derive an optimization framework for computing a view selection policy for streaming multi-view content over a bandwidth constrained channel. The optimization allows us to determine the decisions of sending the packetized data such that the end-to-end r ...

IEEE2013

Model Adequacy for Real-Time Optimization

Dominique Bonvin

Optimization is important in science and engineering as a way of finding ”optimal” situations, designs or operating conditions. Optimization is typically performed on the basis of a mathematical model of the process under investigation. In practice, optimi ...

2012

Real-Time Optimization in the Presence of Uncertainty

Dominique Bonvin

This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. I ...

2012