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A implementation of CF-NADE. Yin Zheng, et. al. "A Neural Autoregressive Approach to Collaborative Filtering", accepted by ICML 2016.
This project forked from ian09/cf-nade
A implementation of CF-NADE. Yin Zheng, et. al. "A Neural Autoregressive Approach to Collaborative Filtering", accepted by ICML 2016.
Code for "A Neural Autoregressive Approach to Collaborative Filtering", ICML 2016 Dependency: You need to install: Theano: http://deeplearning.net/software/theano/ blocks: http://blocks.readthedocs.io/en/latest/bricks_overview.html version 0.1.1 is requred In this code, you can use the code in "datasets" to generate a hdf5 dataset to feed CF-NADE. Then you can run "learner_ordinalcost_directly_itembased_newsoftmax_timing.py" to train and test CF-NADE. And example to run the code is: MovieLens1M=/Users/yin.zheng/ml_datasets/MovieLens1M-shuffle-itembased-0 python learner_ordinalcost_directly_itembased_newsoftmax_timing.py 512 10 60 0.001 0.1 0.001 1e-8 500 tanh 0 0.02 Adam 0 1 0.995 /tmp/cfnade
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