Auto-Sizing Neural Networks: With Applications to n-gram Language Models

Understand

Neural networks have been shown to improve performance across a range of natural-language tasks.

• However, designing and training them can be complicated.
• Frequently, researchers resort to repeated experimentation to pick optimal settings.
• In this paper, we address the issue of choosing the correct number of units in hidden layers.