The aim of this paper is to study an Information Theory based learning theory for neural units endowed with adaptive activation functions. The learning theory has the target to fo...
After a long period when networking research seemed to be focused mainly on making the existing Internet work better, interest in "clean slate" approaches to network arc...
The rapid development of the network technology greatly expands information communication between people and makes the network education become real. Network education has already ...
The key limiting factor in graphical model inference and learning is the complexity of the partition function. We thus ask the question: what are the most general conditions under...
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and signiď¬...