Week 1 Introduction to Discrete Optimization This week we introduce the notion of optimization problems, draw a distinction between continuous and discrete optimization, in- troduce linear programming, and sketch the connection between polyhedral theory and optimization. 1.1 Optimization problems An optimization problem is specified by a set of feasible solutions F and an objective function […]
THE UNIVERSITY OF NEW SOUTH WALES 4. INTEGER MULTIPLICATION II Raveen de Silva, office: K17 202 Course Admin: , School of Computer Science and Engineering UNSW Sydney Term 3, 2021 Table of Contents 1. Recap 2. ’s algorithm 3. Puzzle Basics revisited: how do we multiply two numbers? The primary school algorithm: X X X
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Proving Correctness of Greedy Algorithms COMP3121/9101 21T3 November 27, 2021 This document presents two approaches to prove the correctness of the greedy algorithm presented in lecture 6 for the Activity Selection Problem. These two proofs are written in full detail, using notation to be as precise as possible. Assignment submissions can use worded arguments instead,
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THE UNIVERSITY OF NEW SOUTH WALES 5. THE FAST FOURIER TRANSFORM Raveen de Silva, office: K17 202 Course Admin: , School of Computer Science and Engineering UNSW Sydney Term 3, 2021 Table of Contents 1. Revision 2. The Fast Fourier Transform 3. Puzzle Our strategy to multiply polynomials fast Given two polynomials of degree at
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THE UNIVERSITY OF NEW SOUTH WALES 6. THE GREEDY METHOD Raveen de Silva, office: K17 202 Course Admin: , School of Computer Science and Engineering UNSW Sydney Term 3, 2021 Table of Contents 1. Introduction 2. Example Problems 3. Applications to Graphs 3.1 Single Source Shortest Paths 3.2 Minimum Spanning Trees 4. Puzzle The Greedy
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THE UNIVERSITY OF NEW SOUTH WALES 9. STRING MATCHING Raveen de Silva, office: K17 202 Course Admin: , School of Computer Science and Engineering UNSW Sydney Term 3, 2021 Table of Contents 1. Introduction 2. Hashing 3. Finite Automata 4. Puzzle String Matching algorithms Suppose you have an alphabet S = {s0,s1,…,sd−1} of d characters.
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Discussion 12 1. The bin packing problem is as follows. You have an infinite supply of bins, each of which can hold M maximum weight. You also have n objects, each of which has a (possibly distinct) weight wi (any given wi is at most M). Our goal is to partition the objects into bins,
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THE UNIVERSITY OF NEW SOUTH WALES 7. DYNAMIC PROGRAMMING Raveen de Silva, office: K17 202 Course Admin: , School of Computer Science and Engineering UNSW Sydney Term 3, 2021 Table of Contents 1. Introduction 2. Example Problems 3. Puzzle What is dynamic programming? The main idea is to solve a large problem recursively by building
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Mathematics and Statistics – Design and Analysis of Experiments Week 8 – Factorial Designs (cont. from week 7) Copyright By PowCoder代写 加微信 powcoder Hands-on Activity 1. Conduct a Tukey’s Multiple Comparison procedure to 0. compare three types at Temperature = 70 2. Conduct a Linear and Quadratic Trend analysis of responses in relation to Temperature
1. Introduction and JUnit First Order Logic 1 8/31/21 1 Learning Objectives Differentiate among various logics Express first order logic (FOL) expressions Differentiate syntax vs. semantics of FOL Assess challenges of inference 2 Agenda: First Order Logic 3 Logics Syntax of First Order Logic Semantics of FOL Inference Various Logics 4 Russell & Norvig Example:
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