Introduction to convex optimization

we would like to inform you that starting from March 4th till 15th the following doctoral course will be held. Details are reported below. Title: Introduction to convex optimization Duration: 22 hours, in 8 lectures and 3 lab sessions. Teachers: Saverio Salzo and Silvia Villa. When: time 14:00–16:00, March 4th–8th and 11th–15th. Where: DIBRIS - via Dodecaneso, 35, Room 214. Course webpage: Abstract Convex optimization plays a key role in data sciences. The objective of this course is to provide basic tools and methods at the core of modern nonlinear convex optimization. Starting from the gradient descent method we will cover some state of the art algorithms, including proximal gradient methods, dual algorithms, stochastic gradient descent, and randomized block-coordinate descent methods, which are nowadays very popular techniques to solve machine learning and inverse problems.
Ultimo aggiornamento 28 Febbraio 2019