Harnessing the Power of Noise: A Survey of Techniques and Applications
Abstract
Noise, traditionally considered a nuisance in computational systems, is reconsidered for its unexpected and counter-intuitive benefits across a wide spectrum of domains, including nonlinear information processing, signal processing, image processing, machine learning, network science, and natural language processing. Through a comprehensive review of both historical and contemporary research, this survey presents a dual perspective on noise, acknowledging its potential to both disrupt and enhance performance. Particularly, we highlight how noise-enhanced training strategies can lead to models that better generalize from noisy data, positioning noise not just as a challenge to overcome but as a strategic tool for improvement. This work calls for a shift in how we perceive noise, proposing that it can be a spark for innovation and advancement in the information era.
Fields of Study & Subjects
Machine Learning and Data Classification
Advanced Neural Network Applications
Generative Adversarial Networks and Image Synthesis
Publication details
- Journal / source
- ACM Computing Surveys
- Publisher
- Association for Computing Machinery (ACM)
- Volume
- 58
- Issue
- 13
- Pages
- 1–27
- Publication date
- 7 May 2026
- Language
- EN