Web: http://arxiv.org/abs/2206.11573

June 24, 2022, 1:10 a.m. | Zhiying Jiang, Yiqin Dai, Ji Xin, Ming Li, Jimmy Lin

cs.LG updates on arXiv.org arxiv.org

Most real-world problems that machine learning algorithms are expected to
solve face the situation with 1) unknown data distribution; 2) little
domain-specific knowledge; and 3) datasets with limited annotation. We propose
Non-Parametric learning by Compression with Latent Variables (NPC-LV), a
learning framework for any dataset with abundant unlabeled data but very few
labeled ones. By only training a generative model in an unsupervised way, the
framework utilizes the data distribution to build a compressor. Using a
compressor-based distance metric derived …

arxiv deep latent variable model learning lg model non-parametric parametric

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