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HW1 賴筱婷 周育潤 鄭乃嘉 翁慶年 #4

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HW1 賴筱婷 周育潤 鄭乃嘉 翁慶年 #4

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# Homework1 - Introduce a New NN with Memory
Please complete each homework for each team, and <br>
mention who contributed which parts in your report.
我們介紹的paper"CNN-RNN: A Unified Framework for Multi-label Image Classification"
Baidu Reasch in China發表在CVPR2016

組員:賴筱婷,鄭乃嘉,周育潤,翁慶年

負責部份:

Introduction:賴筱婷

Proposed Method:翁慶年

Experiment and Conclusion:周育潤,鄭乃嘉


# Motivation
NN with Memory can potentially to be used to acompplish many AI related tasks: Reasoning, Decision Making, etc. <br>
Here are some related talks:<br>
本篇論文主要想解決multi-label classification的問題,利用RNN(LSTM)的特性去model label co-occurrence dependency.
* Sumit Chopra from Facebook. Reasoning, Attention and Memory <a href="https://drive.google.com/open?id=0B_wzP_JlVFcKbHdpYVdZMjg3eTBQd2F1OG9QZlVhOGJoX0dz">slides</a>
* Edward Grefenstette from Google DeepMind. Beyond Seq2Seq with Augmented RNNs <a href="https://drive.google.com/open?id=0B_wzP_JlVFcKYTFaTVFJN18tbmtkX2V0WEEtWXVSdDV4UHVZ">slides</a>

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