[talks] Deep learning With ZNN- ROOM CHANGE-now in A02, Princeton Neuroscience Institute

[Michele J. Brown]

The event has been moved to a larger room, PNI A02.  We apologize that
food will not be available until the beginning of the hands-on session
at 1:30pm, as food is not allowed in A02.

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Deep learning with ZNN
Aleksandar Zlateski and Kisuk Lee
October 20, 2014
12pm seminar
1:30pm hands-on session
Princeton Neuroscience Institute A02

Aleks will describe ZNN, his multicore CPU implementation of deep
learning for 2D and 3D convolutional networks.  He will present
preliminary benchmarks showing that ZNN is competitive with
GPU-accelerated deep learning (currently the dominant approach).  The
use of CPUs avoids the limited RAM of GPUs, and reduces software
development cost. Kisuk will present a how-to tutorial on using ZNN,
illustrated with the application of boundary detection in 3D nanoscale
brain images.

The talks will be followed by a hands-on session including
installation of ZNN and application to an image segmentation challenge
(http://brainiac2.mit.edu/isbi_challenge/).[1] Participants should bring
their own laptops, and will require access to their own Linux machine.
Participants are encouraged to install ZNN
(https://github.com/seung-lab/znn-release)[2] prior to the event, as well
as the boost and fftw libraries.