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UID:414@lincs.fr
DTSTART;TZID=Europe/Paris:20181114T140000
DTEND;TZID=Europe/Paris:20181114T140000
DTSTAMP:20190806T140759Z
URL:https://www.lincs.fr/events/tbc-9/
SUMMARY:The Forward-Backward Embedding of Directed Graphs
DESCRIPTION:We introduce a novel embedding of directed graphs derived from
 the singular value decomposition (SVD) of the normalized adjacency matrix.
 Specifically\, we show that\, after proper normalization of the singular
 vectors\, the distancesbetween vectors in the embedding space are
 proportional to the mean commute times between the corresponding nodes by a
 forward-backwardrandom walk in the graph\, which follows the edges
 alternately in forward and backward directions. In particular\, two nodes
 having many commonsuccessors in the graph tend to be represented by close
 vectors in the embedding space. More formally\, we prove that our
 representation of thegraph is equivalent to the spectral embedding of some
 co-citation graph\, where nodes are linked with respect to their common set
 of successors in the original graph. The interest of our approach is that
 it does not require to build this co-citation graph\, which is typically
 much denser than the original graph. Experiments on real datasets show the
 efficiency of the approach.\n\n\nSlides
 The_Forward_Backward_Embedding_of_Directed_Graphs__beamer_Download\n
CATEGORIES:Seminars,Youtube
LOCATION:LINCS / EIT Digital\, 23 avenue d'Italie\, 75013 Paris\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=23 avenue d'Italie\, 75013
 Paris\, France;X-APPLE-RADIUS=100;X-TITLE=LINCS / EIT Digital:geo:0,0
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TZID:Europe/Paris
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DTSTART:20181028T020000
TZOFFSETFROM:+0200
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