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Vincent Vanhoucke
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Lives in San Francisco, CA
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Vincent Vanhoucke

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Female guest: ' I wrote the algorithm.'
Male radio host, sounding incredulous: ' You did?'
Hey +NPR, you're not helping.
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Vincent Vanhoucke

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A geeky deck about street light engineering in San Francisco. Left turns onto one-way streets have always been a puzzling feature of US traffic laws to me. TIL they are actually pretty dangerous.
Every fellow San Franciscan will undoubtedly recognize the Junipero / Sloat / Portola intersection from Hell on slide #12.
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Vincent Vanhoucke

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This is a very neat UI.
 
If you like Wikipedia, try out a site I made for finding all the articles available about some topic.
What is this? This is an experimental interface for finding Wikipedia articles to read when you're doing in-depth research on a topic. Type a topic above to see links to Wikipedia articles that match — English only, for now. As you type, the green bar below the input box will fill with matching ...
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Vincent Vanhoucke

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I'll be at ICML in a few weeks. Come and say hi if you're there!
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Tu y vas direct de CDG ? Prenons un verre si tu passes à Paris
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I agree with some of the reviews: this book should come with a soundtrack. A fantastic read, especially if you know your way around the Berkeley / Oakland area.
<p>As the summer of 2004 draws to a close, Archy Stallings and Nat Jaffe are still hanging in there, long-time friends, bandmates and co-regents of Brokeland Records, a kingdo...
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I quite liked it, although Yiddish Policemen's Union remains my favorite Chabon, and I think Kavalier and Clay was better than this too.
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Back in 2008, when we were working on automatic speech recognition for YouTube, one of my colleagues noticed something uncanny: while our automatic captioning at the time made a mistake approximately every other word on average, when it came to transcribing Sarah Palin's political speeches, it was almost flawless.
My hypothesis was that because her speeches were essentially content-free, our language model could essentially always predict what she was going to say next and make up for our comparatively weak acoustic model.
I think it's time someone puts this hypothesis to the scientific test.
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Your hypothesis makes sense. Presumably the language model does better on basic, generic sentences devoid of sophisticated terminology.
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It's getting harder and harder to stump Google Now.
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Vincent Vanhoucke

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This is the most fun we've had in the office in a while. We've even made some of those 'Inceptionistic' art pieces into giant posters. Beyond the eye candy, there is actually something deeply interesting in this line of work: neural networks have a bad reputation for being strange black boxes that that are opaque to inspection. I have never understood those charges: any other model (GMM, SVM, Random Forests) of any sufficient complexity for a real task is completely opaque for very fundamental reasons: their non-linear structure makes it hard to project back the function they represent into their input space and make sense of it. Not so with backprop, as this blog post shows eloquently: you can query the model and ask what it believes it is seeing or 'wants' to see simply by following gradients. This 'guided hallucination' technique is very powerful and the gorgeous visualizations it generates are very evocative of what's really going on in the network.
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I'd love to see a video of each iteration of the last images to see how they evolve in the neural net. :) Any chance of an upload to YouTube?
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Are you training recurrent neural networks to produce sequences of tokens (like machine translation or image captioning)?
If so, you should read our recent arxiv paper http://arxiv.org/abs/1506.03099 in which we propose a scheduled sampling approach to improve inference in multi-step prediction tasks by reducing the gap between how you train your model and how you use it for inference.
This is joint work with +Oriol Vinyals , +Navdeep Jaitly , and Noam Shazeer. 
Abstract: Recurrent Neural Networks can be trained to produce sequences of tokens given some input, as exemplified by recent results in machine translation and image captioning. The current approach to training them consists in maximizing the likelihood of each token in the sequence given the ...
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I'd not heard of the book before, but I'm starting to think I should check it out.
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I'm happy to announce that our image captioning system based on a paper that we'll present on Tuesday @ CVPR (at 8:30 AM!) won the LSUN competition, where human judges provided us with the "real" metric. For more information with a summary of (most of) recent work, visit:
http://mscoco.org/dataset/#leaderboard-cap

I'm also excited to be at CVPR for the first time! After all the "image captions" papers and research, it'll be nice to see what researchers have in mind for next steps, and to get some feedback from the vision community at large.

+Alexander Toshev +Samy Bengio +Dumitru Erhan 
Download. Begin by downloading the dataset, including the dataset tools, images, and annotations. Learn about the annotation format. See the cocoDemo in either the Matlab or Python code. demo. Evaluate: Format. Develop your algorithm. Run your algorithm on MS COCO and save the results using the ...
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This week, Boston hosts the 2015 Conference on Computer Vision and Pattern Recognition ( #cvpr2015 , http://goo.gl/x59Qmz), the premier annual computer vision event comprising the main CVPR conference and several co-located workshops and short courses. 

As a leader in computer vision research, Google will have a strong presence at CVPR 2015. Head over to the Research blog, linked below, to see the list of publications, workshops and tutorials that Googlers are involved in this year.

If you are attending CVPR this year, we hope you’ll stop by our booth and chat with our researchers about the projects and opportunities at Google that go into solving interesting problems for hundreds of millions of people.  Members of the Jump (http://g.co/jump) team will also have a prototype of the camera on display and will be showing videos produced using the Jump system on Google Cardboard (http://g.co/cardboard).
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Currently
San Francisco, CA
Previously
Very good food. Bring a heavy jacket in the Winter months, this place is freezing and the waiters all wear one.
Public - 5 months ago
reviewed 5 months ago
An avalanche of failures in the peak Holiday season. OpenTable booking broken, you have to go on site. Slow service. Inexperienced, confused looking staff. Tepid potato leek soup, much too salty to eat. Overcooked pasta and fries drowning in salt as well. This might have been a great restaurant in the past, but it's seemingly poorly managed.
Public - 6 months ago
reviewed 6 months ago
Fantastic food. Ever surprising menu. (edit: no longer the Incanto I remember)
Public - a year ago
reviewed a year ago
Indifferent, borderline hostile service. Appetizing menu but poor execution.
Public - a year ago
reviewed a year ago
23 reviews
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A mean hot chocolate.
Public - 11 months ago
reviewed 11 months ago
By far the best meal I've had in Trouville. Don't be in a rush, we were the first in the Restaurant that day and were in there for 1 hour 45 minutes.
Public - a year ago
reviewed a year ago
Very superficial assessment. Tech missed a blatantly ruptured pipe which was pouring air into our crawl space and causing our heating issues. Emails bounce back.
Public - 3 years ago
reviewed 3 years ago