Lecture

Mathematics of Data: Optimization Basics

In course

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Description

This lecture covers some basics on optimization, including linear algebra concepts such as norms, matrix norms, dual norms, and semi-norms. It also delves into the topics of continuity, Lipschitz continuity, differentiation, convexity, and convergence rates. The lecture introduces the concept of L-Lipschitz gradient functions and strong convexity. Various examples and definitions are provided to illustrate these mathematical concepts.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_p36ndyc8

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Ontological neighbourhood

Mathematics

Analysis: Functional analysis, Calculus, Complex analysis

Algebra: Linear algebra

Information engineering

Natural language processing: Topics in natural language processing

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