Semi-supervised Learning

Synonyms

Co-training; Learning from labeled and unlabeled data; Transductive learning

Definition

Semi-supervised learning uses both labeled and unlabeled data to perform an otherwise supervised learning or unsupervised learning task.

In the former case, there is a distinction between inductive semi-supervised learning and transductive learning. In inductive semi-supervised learning, the learner has both labeled training data $\{(x_{i},y_{i})\}_{i=1}^{l}\mathop{ \sim }\limits^{ iid}p(\mathbf{x},y)$ and unlabeled training data $\{\mathbf{x}_{i}\}_{i=l+1}^{l+u}\mathop{ \sim }\limits^{ iid}p(\mathbf{x})$, and learns a predictor $f : \mathcal{X}\mapsto \mathcal{Y},f \in \mathcal{F}$, where $\mathcal{F}$ is the hypothesis space. Here $\mathbf{x} \in \mathcal{X}$ is an input instance, $y \in \mathcal{Y}$ its target label (discrete for classification or continuous for regression), p(x, y) the unknown joint distribution and p(x ) its marginal, and typically l ≪ u. The goal is to...