Lecture 7F (2022-04-12): ANN Reinforcement Learning, Unsupervised Learning, Multidimensional Scaling, & Hebbian/Associative Learning

In this lecture, we introduce applications of ANN outside of conventional supervised learning. In particular, we briefly discuss reinforcement learning (RL and "deep Q-learning") and then introduce unsupervised learning. As examples of unsupervised learning, we discuss clustering, autoencoders, and multidimensional scaling (MDS). We end with a brief introduction to Hebbian/associative learning, which will be picked up next time as we start talking about spiking neural networks (and spike-timing-dependent plasticity, STDP).

Whiteboard notes for this lecture can be found at: https://www.dropbox.com/s/a4l4k7rs589jcjn/IEE598-Lecture7F-2022-04-12-ANN_Reinforcement_Learning-Unsupervised_Learning-Multidimensional_Scaling-and-Hebbian_Associative_Learning.pdf?dl=0