[Lisa_teatalk] [Lisa_labo] talk this Thursday 16th 13:00 - Ian Goodfellow

Çağlar Gülçehre ca9lar at gmail.com
Thu Jan 16 15:39:38 EST 2014


As a related note, I think it is also possible to learn parse trees (hence
the tree data structure) using reinforcement learning for images and
natural language,

For images:
http://vision.mas.ecp.fr/Personnel/teboul/files/cvpr11_teboul.pdf

For natural language processing, I think Hal Daume published a few papers
with imitation learning.

But these examples are not using neural networks.



On Thu, Jan 16, 2014 at 2:09 PM, Yoshua Bengio <yoshua.bengio at gmail.com>wrote:

> Here is the paper I mentioned during Ian's presentation about training a
> recurrent net to exploit a push-pop stack:
>
> http://books.nips.cc/papers/files/nips02/0380.pdf
>
> It was not Mike Mozer but Lee Giles.
>
> -- Yoshua
>
>
>
> On Mon, Jan 13, 2014 at 1:04 PM, Razvan Pascanu <r.pascanu at gmail.com>wrote:
>
>> Hi all,
>>
>>  First of all the schedule has changed, and tea talks will be Wednesdays
>> from 13-14 from now on.
>>
>> There is an exception this week. We will have Ian presenting this
>> **Thursday from 13:00 to 14:00**.
>> Speaker: Ian Goodfellow
>>
>> Title: Ian's ideas for research projects
>>
>> Abstract:
>>
>> I'll throw out a few of my recent ideas for research
>> projects, ranging from easy to idealistic:
>> -Restricted maxout units
>> -Regularizing piecewise linear nets to change pieces rarely
>> -Sparsely connected recurrent nets
>> -Trajectory optimization for recurrent nets
>> -"Cognitive agency" and how you can use it to do things like
>> discrete-state nets, dynamically structured nets, and nets that
>> interact with data structures like stacks and tapes
>>
>> I hope to see many of you there. And please register for giving tea
>> talks.
>>
>> Razvan
>>
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>>
>>
>
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-- 
Caglar GULCEHRE
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