BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//talks.cam.ac.uk//v3//EN
BEGIN:VTIMEZONE
TZID:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:19700329T010000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:19701025T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Networks as signals: Extraction of dynamical netwo
rk structures - Pierre Borgnat (ENS - Lyon\; CNRS
(Centre national de la recherche scientifique))
DTSTART;TZID=Europe/London:20161214T140000
DTEND;TZID=Europe/London:20161214T144500
UID:TALK69496AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/69496
DESCRIPTION:Joint work with Ronan Hamon (LIF\, Marseille\, Fra
nce)\, P. Flandrin (CNRS\, LP\, ENS de Lyon\, Fran
ce) and C. Robardet (LIRIS\, INSA de Lyon\, France
)
We have proposed  \;a \;new fra
mework to track the structure of temporal networks
\, using \;a signal processing approach: the m
ethod is based on the duality between static netwo
rks and signals using a multidimensional scaling t
echnique. For temporal networks\, it enables \
;a tracking of the network structure over time. To
extract the most significant patterns of the netw
orks \;and their activation over time\, we use
 \;nonnegative matrix factorization of the tem
poral spectra. This framework\, inspired by audio
decomposition\, allows transforming back these fre
quency patterns into networks\, so as \;to hig
hlight the evolution of the underlying structure o
f the network over time. The effectiveness of the
method is first evidenced on a toy example\, prior
being used to study a temporal network of face-to
-face contacts. The extraction of sub-networks hig
hlights significant structures decomposed on time
intervals. \;
LOCATION:Seminar Room 1\, Newton Institute
CONTACT:INI IT
END:VEVENT
END:VCALENDAR