We are happy to announce a seminar on Optimization and Machine Learning Seminar organized by Corelab at NTUA. The goal of this seminar is to introduce the basic concepts of machine learning and convex optimization.
Automated Learning, or Machine Learning as it is usually called, describes the development of algorithmic procedures that convert experience to expertise. Usually, machine learning procedures are inspired by algorithms used in convex optimization.
In convex optimization we explore algorithmic procedures to optimize convex functions over continous convex domains. Apart from the applications of convex optimization to machine learning, during the last decade there has been a great amount of research on using convex optimization for solving combinatorial optimization problems.
The program of the seminar is described in detail below and involves: (1) the basic definitions and concepts of theoretical machine learning, (2) introduction to convex optimization and basic applications to solving combinatorial problems, (3) the basic definitions, techniques and open problems of deep learning.
If you would like to participate in our seminar please register here.
We will assume that all participants are familiar with the following concepts:
Room 004 at School of Electrical and Computer Engineering [Directions].