[Lisa_seminaires] UdeM-McGill-MITACS machine learning seminar Wed Aug. 24th @ 15h00, AA3195

Guillaume Desjardins guillaume.desjardins at gmail.com
Lun 22 Aou 18:16:47 EDT 2011


A new school year is upon us, and with it, comes a new round of seminars !

I am thus pleased to announce that a UdeM-McGill-MITACS machine learning
seminar will be held this Wesdnesday, Aug 24th. The talk will be given by
Benjamin Schrauwen and take place from 15h00-16h00 in the room AA3195
(pavillon Andre-Aisenstadt, click
here<http://maps.google.ca/maps?q=2920,+chemin+de+la+tour&hl=en&z=16&iwloc=A>for
directions) at the Université de Montréal. Abstract and title below.
Hope to see you there !


Title: An overview and recent insights on Reservoir Computing

Abstract:

Many practical and industrial applications are temporal in nature: control,
model identification, robotics, language processing, speech recognition,
biomedical signal processing, ... Reservoir Computing (RC) is a recently
proposed Machine Learning technique using untrained recurrent neural
networks as feature expansion which allows to train spatio-temporal
functionals using only linear regression.

We will introduce the technique and show various tasks on which it has been
successfully applied. Recent work will be presented that shows that kernel
functions can be defined that effectively simulate infinite sized reservoir
systems, and how RC can be seen as fading memory regularizers.

If time permits, we will briefly demonstrate that the ideas of Reservoir
Computing can lead to a radically new way of thinking about how computation
can be implemented in physical systems.
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