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View Code? Open in Web Editor NEWCode of our paper "Attribute Graph Neural Networks for Strict Cold Start Recommendation" accepted by TKDE 2020.
Code of our paper "Attribute Graph Neural Networks for Strict Cold Start Recommendation" accepted by TKDE 2020.
请问大佬,如何通过ml100k\source_data——》生成模型训练所需的数据的?可否更新上传数据处理代码?
can you share processed movielens-1M dataset? Thanks!
In standard VAE, it's item_var instead of item_z,
kl_loss = torch.mean(0.5 * torch.sum(torch.exp(item_z) + item_mu ** 2 - 1. - item_var, 1)) +
torch.mean(0.5 * torch.sum(torch.exp(user_z) + user_mu ** 2 - 1. - user_var, 1))
"""
Hence we require the reconstructed embedding x′u to be similar with both the preference embed- ding (by the constraint) and the original attribute distribution (by the standard VAE). To summarize, the reconstruction loss function in our proposed eVAE is defined as follows.
where the first two terms are same as those in standard VAE, and the last one is our extension for the approximation part.
"""
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