Convex optimization edx

St, where St= {x| − 1 ≤ (cost, ,cosmt) Tx≤ 1}, and so is convex

The definition and the set are illustrated in figures 2

13 and 2 14, for m= 2

In the examples above we establish convexity of a set by expressing it as a (possibly infinite) intersection of halfspaces

One of the case of it is convex optimization problem which is a problem of minimizing convex functions over convex sets

17' Inception (-v4, -ResNet) (writing

) Keras (writing

) When we solve machine learning problem, we have to optimize a certain objective function

Introductory Lectures on Convex Optimization: A Basic Course ISBN 978-1-4613-4691-3 ISBN 978-1-4419-8853-9 (eBook) DOI 10

1007/978-1-4419-8853-9 Copyright Cl 2004 by Springer Science+Business Media New York Originally published by Kluwer Academic Publishers in 2004 Softcover reprint of the hardcover 1st edition 2004 All rights reserved