Amnon Shashua, On the Expressive Power of ConvNets and RNNs, Technion, CS, Tuesday 23/01/2018, 10:30

[Michael Zibulevsky]

  

Date: Sun, Dec 31, 2017 at 1:33 PM
Subject: Amnon Shashua - COLLOQUIUM LECTURE - RESCHEDULED - NOTE UNUSUAL TIME AND PLACE on Tuesday 23/01/2018
To: CS-CO...@listserv.technion.ac.il


Time+Place : Tuesday 23/01/2018 10:30 room Auditorium 2 Taub  Bld.
Speaker    : Amnon Shashua - COLLOQUIUM LECTURE - NOTE UNUSUAL TIME AND
PLACE
Affiliation: Hebrew University; CEO & CTO, Mobileye; Senior Vice President,
Intel Corporation
Host       : Ron Kimmel
Title      : On the Expressive Power of ConvNets and RNNs as a Function of
their Architecture

Abstract   :

Expressive efficiency refers to the relation between two architectures A and
B, whereby any function realized by B could be replicated by A, but there
exists functions realized by A, which cannot be replicated by B unless its
size grows significantly larger. For example, it is known that deep networks
are exponentially efficient with respect to shallow networks, in the sense
that a shallow network must grow exponentially large in order to approximate
the functions represented by a deep network of polynomial size. In this
work, we extend the study of expressive efficiency to the attribute of
network connectivity and in particular to the effect of "overlaps" in the
convolutional process, i.e., when the stride of the convolution is smaller
than its filter size (receptive field).  Our analysis shows that having
overlapping local receptive fields, and more broadly denser connectivity,
results in an exponential increase in the expressive capacity of neural
networks. Moreover, while denser connectivity can increase the expressive
capacity, we show that the most common types of modern architectures already
exhibit exponential increase in expressivity, without relying on
fully-connected layers.

Joint work with Or Sharir

Short Bio:
==========
Amnon Shashua holds the Sachs chair in computer science at the Hebrew
University. He received his Ph.D. degree in 1993 from the AI lab at MIT
working on computational vision where he pioneered work on multiple view
geometry and the recognition of objects under variable lighting. His work on
multiple view geometry received best paper awards at the ECCV 2000, the Marr
prize in ICCV
2001 and the Landau award in exact sciences in 2005. His work on Graphical
Models received a best paper award at the UAI 2008. Prof. Shashua was the
head of the School of Engineering and Computer Science at the Hebrew
University of Jerusalem during the term 2003-2005. He is also well known on
founding startup companies in computer vision and his latest brainchild
Mobileye employs today 250 people developing systems-on-chip and computer
vision algorithms for detecting pedestrians, vehicles, and traffic signs for
driving assistance systems. For his industrial contributions prof. Shashua
received the 2004 Kaye Innovation award from the Hebrew University.

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Refreshments will be served from 10:15
Lecture starts at 10:30

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