[AI Seminar] ai-seminar-announce Digest, Vol 78, Issue 1

[Adams Wei Yu]

A gentle reminder that the talk will happen tomorrow (Tuesday) noon in NSH
1507 (unusual place).

On Sun, Nov 5, 2017 at 10:00 AM, <ai-seminar-announce-request at cs.cmu.edu>
wrote:

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>    1.  AI Seminar sponsored by Apple -- Hanxiao Liu -- Nov 07
>       (Adams Wei Yu)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Sat, 4 Nov 2017 05:13:58 -0600
> From: Adams Wei Yu <weiyu at cs.cmu.edu>
> To: ai-seminar-announce at cs.cmu.edu
> Subject: [AI Seminar] AI Seminar sponsored by Apple -- Hanxiao Liu --
>         Nov 07
> Message-ID:
>         <CABzq7ep-Wcy=9x+GLOx91jNOnJW6YdEmu+6YAaGNxjAoONm51w at mail.gmail.
> com>
> Content-Type: text/plain; charset="utf-8"
>
> Dear faculty and students,
>
> We look forward to seeing you next Tuesday, Nov 07, at noon in NSH 1507
> (unusual place) for AI Seminar sponsored by Apple. To learn more about the
> seminar series, please visit the AI Seminar webpage
> <http://www.cs.cmu.edu/~aiseminar/>.
>
> On Tuesday, Hanxiao Liu <http://www.cs.cmu.edu/~hanxiaol/> will give the
> following talk:
>
> Title: Hierarchical Representations for Efficient Architecture Search
>
> Abstract:
>
> We explore efficient neural architecture search methods and present a
> simple yet powerful evolutionary algorithm that can discover new
> architectures achieving state of the art results. Our approach combines a
> novel hierarchical genetic representation scheme that imitates the
> modularized design pattern commonly adopted by human experts, and an
> expressive search space that supports complex topologies. Our algorithm
> efficiently discovers architectures that outperform a large number of
> manually designed models for image classification, obtaining top-1 error of
> 3.6% on CIFAR-10 and 20.3% when transferred to ImageNet, which is
> competitive with the best existing neural architecture search approaches
> and represents the new state of the art for evolutionary strategies on this
> task. We also present results using random search, achieving 0.3% less
> top-1 accuracy on CIFAR-10 and 0.1% less on ImageNet whilst reducing the
> architecture search time from 36 hours down to 1 hour.
>
> This is joint work with Karen Simonyan, Oriol Vinyals, Chrisantha Fernando
> and Koray Kavukcuoglu at DeepMind.
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> End of ai-seminar-announce Digest, Vol 78, Issue 1
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