Training Strategies on English AI Terms Dictionary

Semi-supervised learning

Sat, 18 Jul 2026 10:15:05 +0000

Definition

Semi-supervised learning is a hybrid training paradigm that utilizes a small amount of labeled data alongside a large volume of unlabeled data. The core assumption is that the structure of the unlabeled data can help define decision boundaries more effectively than labeled data alone. Techniques such as self-training, co-training, and graph-based methods are commonly used. This approach is valuable when labeling data is expensive or time-consuming, allowing models to achieve performance close to fully supervised methods with significantly fewer labeled examples.

Multitask optimization

Sat, 18 Jul 2026 10:08:53 +0000

Definition

Multitask optimization involves training a single model to handle several distinct but related tasks at once. By sharing intermediate representations across tasks, the model can learn more generalized features that benefit all associated objectives. This approach often leads to improved performance compared to training separate models for each task, as it reduces overfitting and leverages commonalities between tasks. It is particularly useful when data for individual tasks is limited or when computational efficiency is a priority.