Algorithm design and analysis is fundamental to all areas of computer science and gives a rigorous framework for the study optimization. This course provides an introduction to algorithm design ...
This is an introductory course on algorithms at the graduate level. It assumes familiarity with basic data structures such as lists, queues, trees and graphs, and emphasizes creativity in the design ...
15-451/651 is an advanced undergraduate/masters algorithms class. We cover fundamental algorithmic modeling techniques (e.g. dynamic programming, graphs, network flows, linear programming), advanced ...
Homework problems are weighted by their point values. The two midterm exams will be weighted based on whichever you perform better on. We will give a higher weight to the exam on which you earn a ...
The course provides a review of general algorithm classes such as dynamic programming ... if you sit the exam for one of the following courses: INF3130 – Algoritmer: Design og effektivitet ...
This has had most effect on semialgebraic proof systems and linear and semidefinite programming. This monograph details the interplay between proof systems and efficient algorithm design and surveys ...
The first step for implementing the MapReduce algorithm design pattern is to split the input data into smaller and independent chunks, called splits. Each split can be stored on a different node ...
Abstract: We present a basic algorithm for optimal experimental design in distributed fibre-optic sensing. It is based on the fast random generation of fibre-optic cable layouts that can be tested for ...
Probabilistic analysis is a way of measuring the performance of an algorithm based on the likelihood of different inputs and outcomes. It assumes that the input data is drawn from a known ...