Deep Reinforcement One-Shot Learning for Artificially Intelligent Classification Systems

Understand

In recent years there has been a sharp rise in networking applications, in which significant events need to be classified but only a few training instances are available.

• These are known as cases of one-shot learning.
• Examples include analyzing network traffic under zero-day attacks, and computer vision tasks by sensor networks deployed in the field.
• To handle this challenging task, organizations often use human analysts to classify events under high uncertainty.