meeting this week
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Leif Johnson
Sep 30, 2014, 5:42:47 PM9/30/14
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Hi everyone!
Our next meeting will be this Friday, 3 October, at 10am in GDC 3.516.
We'll have some bagels and cream cheese and discuss the following
paper:
http://arxiv.org/abs/1302.4389
Maxout Networks
Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville,
Yoshua Bengio
We consider the problem of designing models to leverage a recently
introduced approximate model averaging technique called dropout. We
define a simple new model called maxout (so named because its output
is the max of a set of inputs, and because it is a natural companion
to dropout) designed to both facilitate optimization by dropout and
improve the accuracy of dropout's fast approximate model averaging
technique. We empirically verify that the model successfully
accomplishes both of these tasks. We use maxout and dropout to
demonstrate state of the art classification performance on four
benchmark datasets: MNIST, CIFAR-10, CIFAR-100, and SVHN.
--
http://www.cs.utexas.edu/~leif
Our next meeting will be this Friday, 3 October, at 10am in GDC 3.516.
We'll have some bagels and cream cheese and discuss the following
paper:
http://arxiv.org/abs/1302.4389
Maxout Networks
Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville,
Yoshua Bengio
We consider the problem of designing models to leverage a recently
introduced approximate model averaging technique called dropout. We
define a simple new model called maxout (so named because its output
is the max of a set of inputs, and because it is a natural companion
to dropout) designed to both facilitate optimization by dropout and
improve the accuracy of dropout's fast approximate model averaging
technique. We empirically verify that the model successfully
accomplishes both of these tasks. We use maxout and dropout to
demonstrate state of the art classification performance on four
benchmark datasets: MNIST, CIFAR-10, CIFAR-100, and SVHN.
--
http://www.cs.utexas.edu/~leif
Leif Johnson
Oct 2, 2014, 3:18:52 PM10/2/14
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