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Bradley Neuberg
Worked at Google Inc.
Attended Columbia University
Lives in San Francisco, California
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I'm working on a neural network that can take two segmented facial images as input and return a binary "same/not same" answer on whether the two given images are the same person or not. Is anyone aware of any prior work in the literature that can help provide direction on a best approach to this?
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Chris Russell's profile photoMilan Lajtoš's profile photoBradley Neuberg's profile photoPatrick Ehlen's profile photo
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Chris that paper looks incredible; thanks for pointing that out to me. Milan, Siamese networks look like a good fit; there's even a Caffe model checked into the Caffe repo recently I can use.
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Bradley Neuberg

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Can Caffe be used for Recurrent Neural Networks (RNN)? If not, what are most people in the field using to model their RNNs?
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Will Williams's profile photoSoumith Chintala's profile photoMin Ooch's profile photoMariano Phielipp's profile photo
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Check out the pull requests for caffe, there s one pending for integration that brings RNN and LSTM to cafe.
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Bradley Neuberg

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Does anyone know if it's easy to generate charts from Caffe, such as seeing how the error rate changes over training epochs for the test and cross validation data sets? Seems like it's necessary to generate these charts as one tunes the hyperparameters of a neural network to be understand how they effect things.
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For future reference for others, here's an example summary of how you can capture Caffe's output, run it through the parse_log.sh script, and then make a simple plot of the results:

./examples/mnist/train_lenet.sh 2>&1 | tee "mnist.log"
./tools/extra/parse_log.sh ./mnist.log
gnuplot ./tools/extra/plot_log.gnuplot.example

You'll want to customize the plot_log.gnuplot.example file for your own uses. The 'tee' command will also print out the results as they run as well as save them to a file, so you can follow training as it happens.
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From Thailand, to Coworking, to HTML5, Now to Next Generation eBooks: Refocusing My Blog
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Bradley Neuberg

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We just announced what I've been working on the last year! It's called Inkling Habitat (http://www.inkling.com/habitat/), and its the world's first browser-based scalable publishing environment for interactive content. It's nice to be able to talk about what I'm working on now :)
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Michael[tm] Smith's profile photoDavid Dailey's profile photohtml5.org's profile photoLuther Huffman's profile photo
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HeyYa - Videos for "Social Learning Network" and "Unfair Advantage" (Gotta change that text; not real meaningful / slightly misleading) have me doing back-flips here! <inkling.com/features>
(DM to you in Twitter)

I just did Harvard's "Justice" course with Michael Sandel. Wonderful material. But OMG the edX system they use is like ... like something created in 1998. Painfully Web0.6b. <edx.org>

p.s. RFE: you should use avatar from Twitter or pic from Blog here! When I see that default pic I take it to mean "Account Inactive". cheers
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A nice and largely accurate article in The Chronicle of Higher Education about the history of neural nets and deep learning, with quotes from +Geoffrey Hinton, +Terrence Sejnowski, +Yoshua Bengio, and yours truly.

http://chronicle.com/article/The-Believers/190147/
The hidden story behind the code that runs our lives.
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I'm working through Geoffrey Hinton's 2012 Coursera course on Neural Networks. In the course he mentions the exploding and vanishing gradient problem when working with Recurrent Neural Networks. He gives several solutions to this, including careful default initialization + momentum, using Hessian Free optimization, LSTMs, and Echo State Networks. What is the current state of the art when dealing with RNNs? Are these still the grab bag of techniques one would reach for or are there other, simpler options now? Are Echo State Networks still used, as their generality seems limited?
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Jim Fan
 
+Junyoung Chung Oh sorry about that, I didn't really read through the paper in details, just heard about it from a friend. 
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Peter Diamandis always has unique, positive ideas for the future, and the elbow grease to back them up with action. Looks like this will be a great event.
 
Join Peter H. Diamandis to discuss Abundance, exponential technologies and anything else.
Hangout With Peter Diamandis
Thu, June 20, 2013, 12:00 PM EDT
Hangouts

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McAllen, Texas - New York, NY - Kamala, Phuket, Thailand - Esalen, California
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Brad