The Variational Fair Autoencoder

We investigate the problem of learning representations that are invariant to certain nuisance or sensitive factors of variation in the data while retaining as much of the remaining information as possible. Our model is based on a variational autoencoding architecture with priors that encourage independence between sensitive and latent factors of variation... (read more)

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Datasets


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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Sentiment Analysis Multi-Domain Sentiment Dataset VFAE DVD 76.57 # 3
Books 73.40 # 3
Electronics 80.53 # 2
Kitchen 82.93 # 3
Average 78.36 # 4

Methods used in the Paper


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