Collection

Special Issue: Reliability and Statistical Computing

Submission status
Closed

We're living in an era of fast and unpredictable change. Billions of people are connected to each other through their mobile devices and the Internet of Everything (IoE). Data is being collected and processed like never before. The era of AI through reliability and statistical machine computing as well as intelligent and recommender systems with almost all applications and service industry has experienced a dramatic shift in the past two decades to a truly global industry, known as the Industry 4.0. The forces that have driven this change are still at play and will continue. Most of the products that affect our daily lives are becoming even more complex than ever.

Articles concerning new theoretical research and methods on reliability and statistical computing are solicited. Preference will be given to papers with real-world applications over purely theoretical papers. Topics of interest include, but are not limited to:

• Mathematical and statistical methods in reliability

• Big data modeling and prediction

• Statistical learning algorithms, models and theories

• Machine learning theories, models and systems

• Large scale optimization

• Text mining and deep machine learning

• Reliability and dependability of intelligent systems

• Reliability modeling and optimization

• Causal embeddings for recommendation

• Statistical inference for recommendation systems

Applications

• Best practices and lessons learned on developing products in complex systems

• Industrial Case Studies in Intelligent systems

• Internet of Everything (IoE) applications

• Optimization techniques in machine learning

Call for Papers Flyer: Reliability and Statistical Computing

Editors

Articles (23 in this collection)