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Preparing Smart Environments for Life in the Wild: Feature-space and Multi-view Heterogeneous Transfer Learning
With the ever-increasing abundance of sensing and computing devices embedded into our environments we have the opportunity to create personalized activity recognition ecosystems. Two key challenges must first be overcome, ...
POLICY ADVICE, NON-CONVEX AND DISTRIBUTED OPTIMIZATION IN REINFORCEMENT LEARNING
Transfer learning is a method in machine learning that tries to use previous training knowledge to speed up the learning process. Policy advice is a type of transfer learning method where a student agent is able to learn ...
Efficient Machine Learning Algorithms for Automatic Reconfiguration of Mobile Health Monitoring Systems
Mobile health monitoring plays a central role in a variety of healthcare applications. Due to the sensitive nature of healthcare applications, these systems need to process these personal and physiological informations ...
Knowledge Transfer in Reinforcement Learning: How agents should benefit from prior knowledge
Reinforcement learning (RL) has had many successes in different tasks, but in practice, it often requires significant amounts of data or training time to learn high-performing policies. For complicated tasks, the learning ...