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Adaptive Hyperparameter Optimization for Continual Learning Scenarios
This paper aims to explore the role of hyperparameter selection in continual learning and the necessity of continually and automatically tuning them according to the complexity of the task at hand.
Continual Learning for Predictive Maintenance: Overview and Challenges
In this work, we present a brief introduction to predictive maintenance, non-stationary environments, and continual learning, together with an extensive review of the current state of applying continual learning in real-world applications and specifically in predictive maintenance.
Continual-Learning-as-a-Service (CLaaS): On-Demand Efficient Adaptation of Predictive Models
The two main future trends for companies that want to build machine learning-based applications and systems are real-time inference and continual updating.
AI-as-a-Service Toolkit for Human-Centered Intelligence in Autonomous Driving
This paper presents a proof-of-concept implementation of the AI-as-a-Service toolkit developed within the H2020 TEACHING project and designed to implement an autonomous driving personalization system according to the output of an automatic driver's stress recognition algorithm, both of them realizing a Cyber-Physical System of Systems.
