Lecture

Complexity of Algorithms: Big-O

In course

Cillum nisi ullamco irure anim adipisicing minim elit fugiat consequat magna. Anim voluptate nulla minim occaecat eiusmod commodo officia ad. Sunt consequat sunt ad id proident eiusmod commodo occaecat laborum Lorem fugiat occaecat ut magna. Magna mollit ea ex labore qui.

Description

This lecture covers the concept of Big-O notation, illustrating how to determine the complexity of algorithms by analyzing polynomials. Through examples and proofs, the instructor explains how to identify the dominant terms in polynomials and their growth rates.

Official source

https://mediaspace.epfl.ch/media/0_lomd04vz

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Theoretical computer science

Theory of computation: Computational complexity theory

Mathematics

Analysis: Numerical analysis

Related lectures (42)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.