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The implementation the paper 'Learning Deep Latent Spaces for Multi-Label Classifications' in AAAI 2017

MATLAB 94.44% C 5.21% M 0.21% Python 0.14%

c2ae's Introduction

C2AE

This is an implementation of the paper

Chih-Kuan Yeh*, Wei-Chieh Wu*, Wei-Jen Ko, Yu-Chiang Frank Wang 'Learning Deep Latent Spaces for Multi-Label Classfications' published in AAAI 2017 (* indicated equal contribution)

We thank Weiran Wang, Raman Arora, Karen Livescu and Jeff Bilmes for the layout of the matlab code in http://ttic.uchicago.edu/~wwang5/dccae.html

Chih-Kuan Yeh thanks his co-author of the papers, Wei-Chieh Wu who contributed significantly to modifying the layout of the program.

The code is further polished by Chih-Kuan Yeh.

If you have any questions regarding the code please contact Chih-Kuan Yeh at [email protected]

The demo code is ran on parsed dataset of mirflickr, which can easily be applied on other multi-label datasets by including the .mat file and modifying demo.m

Simply run demo.m to see the results on mirflickr.

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