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Publications associées (25)

Population Sensing Using Mobile Devices : a Statistical Opportunity or a Privacy Nightmare?

Farid Movahedi Naini

In our daily lives, our mobile phones sense our movements and interactions via a rich set of embedded sensors such as a GPS, Bluetooth, accelerometers, and microphones. This enables us to use mobile phones as agents for collecting spatio-temporal data. The ...

EPFL2014

Analysis of Fitness Noise in Particle Swarm Optimization: From Robotic Learning to Benchmark Functions

Alcherio Martinoli, Inaki Navarro Oiza, Ezequiel Leonardo Di Mario

Population-based learning techniques have been proven to be effective in dealing with noise and are thus promising tools for the optimization of robotic controllers, which have inherently noisy performance evaluations. This article discusses how the result ...

2014

Intensive Surrogate Model Exploitation in Self-adaptive Surrogate-assisted CMA-ES (saACM-ES)

Ilya Loshchilov

This paper presents a new mechanism for a better exploitation of surrogate models in the framework of Evolution Strategies (ESs). This mechanism is instantiated here on the self-adaptive surrogate-assisted Covariance Matrix Adaptation Evolution Strategy (( ...

Assoc Computing Machinery2013

Competing islands limit the rate of adaptation in structured populations

Cornelia Pokalyuk

Beneficial mutations can co-occur when population structure slows down adaptation. Here, we consider the process of adaptation in asexual populations distributed over several locations ("islands"). New beneficial mutations arise at constant rate u(b), and ...

Elsevier2013

CMA-ES with Restarts for Solving CEC 2013 Benchmark Problems

Ilya Loshchilov

This paper investigates the performance of 6 versions of Covariance Matrix Adaptation Evolution Strategy (CMAES) with restarts on a set of 28 noiseless optimization problems (including 23 multi-modal ones) designed for the special session on real-parameter ...

2013

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