Machine Intelligence and Information Theory Lab @ UNIST Graduate School of AI & Department of EE
We cover the range of distributed optimization in the traditional cases and the recent achievements of federated learning, which is the framework to enable decentralized AI.
It covers basic programming tools for electrical engineering (C++).
It covers various kinds of algorithms for meta & multi-task learning and their underlying theories.
We consider machine learning algorithms for capturing generalization across varying tasks.
It covers the range of basic mathematics and programming for machine learning algorithms to deep learning architectures such as CNN and RNN.