Few-Shot Non-Parametric Learning with Deep Latent Variable Model. (arXiv:2206.11573v1 [cs.LG])

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 latent variable model learning lg non-parametric parametric