ICLR 2018 Chin-Chia Michael YehYan ZhuEvangelos E. PapalexakisAbdullah MueenEamonn Keogh

We propose a novel unsupervised representation learning framework called neighbor-encoder in which domain knowledge can be trivially incorporated into the learning process without modifying the general encoder-decoder architecture. In contrast to autoencoder, which reconstructs the input data, neighbor-encoder reconstructs the input data's neighbors... (read more)

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