Plan School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 4 13–17 August 2018 We provide more exercises than we can cover in the tutorial, so that you have more to practice on in your own time. The exercises 15. For each of the following pairs f, g, determine whether f(n) ∈ […]
Plan School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 3 6–10 August 2018 Last week’s lecture discussed asymptotics and the mathematical analysis of algorithms; this week’s lectures will be about brute force methods and recursion. This week’s questions 12–14 are combinatorics-style puzzles. Good problem-solving fun, but not essential. The exercises 7.
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COMP90038 Algorithms and Complexity Lecture 17: Hashing (with thanks to Harald Søndergaard & Michael Kirley) Andres Munoz-Acosta munoz.m@unimelb.edu.au Peter Hall Building G.83 Recap • We talked about using some memory space (in the form of extra tables, arrays, etc.) to speed up our computation. • Memory is cheap, time is not. • Sorting by counting
Plan School of Computing and Information Systems COMP90038 Algorithms and Complexity Tutorial Week 11 8–12 October 2018 The exam is not far away, so keep up with tutorials; as always, try tackling the problems before the tute. The exercises 74. Use the dynamic-programming algorithm developed in Lecture 18 to solve this instance of the coin-row
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QUESTION: A Loading Problem: We are given a set S of n items with weights specified by positive real numbers wi , i=1..n, and a truck with load weight capacity specified by a positive real number L. We want to load the truck with as many items as possible without exceeding its load capacity. That
Assignment specification. Assignment 2 Spatial and Top-k search algorithms Due Date: Oct 31st, 2018 5:00pm The goal of this assignment is the development and testing of spatial and top-k search algorithms. Dataset. For this assignment, you will have to browse to http://www.cs.utah.edu/~lifeifei/SpatialDataset.htm and download two files using the following links: California Road Network’s Nodes (Node