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Resources for RNN

rnn-project 최신버젼 다운로드

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// repository documentation

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# rnn-project
This is a repository for rnn-related papers and techniques.

# basic concepts:
1. [Mechanisms of LSTM][1]

# deep-framework
1. NVIDIA DIGITS + Caffe/Torch
	- [On an Amazon EC2 instance][2]
	- [DIGIT3][3]
	- [NVIDIA/DIGITS.GitHub][4]

2. [CaffeOnSpark][5]

# top conferences
1. [IJCAI][6]
	- Paper Dealine: February 19, 2016
	- Rebuttal Period: March 10-11, 2016
2. [ICLR][7]
	- Paper Deadline: 
		- title, abstract, preliminary draft: November 12th, 2015
		-  arXiv paper ID and final draft: November 19th, 2015

3. [AAAI][8]
	- Paper Deadline 
		- abstract: September 10, 2015
		- final: September 15, 2015

# keep up with trends
1. [keep with new trends][9]
2. [future of AI from LeCun][10]
3. Large-Scale Deep Learning for Intelligent Computing Systems
	- From **Jeff Dean**
	- [slides][11] and [video][12]

[1]:	https://www.quora.com/How-does-LSTM-help-prevent-the-vanishing-and-exploding-gradient-problem-in-a-recurrent-neural-network
[2]:	http://www.learnopencv.com/nvidia-digits-3-on-ec2/
[3]:	https://developer.nvidia.com/digits
[4]:	https://github.com/NVIDIA/DIGITS
[5]:	https://github.com/yahoo/CaffeOnSpark
[6]:	http://ijcai-16.org/index.php/welcome/view/home
[7]:	http://www.iclr.cc/doku.php
[8]:	http://www.aaai.org/Conferences/AAAI/aaai16.php
[9]:	http://handong1587.github.io/deep_learning/2016/04/01/keep-up-with-new-trends.html
[10]:	http://mp.weixin.qq.com/s?__biz=MzI3MTA0MTk1MA==&mid=403182818&idx=1&sn=7d4a8f11e61573183c1797addaacf937&scene=0#wechat_redirect
[11]:	http://www.slideshare.net/hustwj/cikm-keynotenov2014
[12]:	https://www.youtube.com/watch?v=4hqb3tdk01k

rnn-project

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