PPIA

Copy of COMP3010 - 7.2 - Huffman Encoding

COMP3010 - 13.0 - Summary

COMP3010 - 12.0 - Approximation Algorithm

COMP3010 - 11.2 - Reduction

COMP3010 - 11.1 - NP-Completeness and Reduction

COMP3010 - 11.0 - P vs NP

COMP3010 - 9.2 - Randomised Algorithms

COMP3010 - 9.1 - Probabilistic Analysis

COMP3010 - 9.0 - Basic Probability

COMP3010 - 8.4 - Floyd-Warshall Algorithm

COMP3010 - 8.3 - Matrix Multiplication Method

COMP3010 - 8.2 - Bellman-Ford Algorithm

COMP3010 - 8.1 - Single-Source Shortest Path

COMP3010 - 8.0 - Maximum Flow

COMP3010 - 7.0 - LCSS

COMP3010 - 7.1 - Edit Distance

COMP3010 - 7.2 - Huffman Encoding

COMP3010 - 2.4 - Correctness of Iterative Algorithms

COMP3010 - 6.3 - Master Method

The master method formula

COMP3010 - 6.2 - Substitution Method

Substitution method for finding the running time of a divide and conquer algorithm

COMP3010 - 6.1 - Recursion Tree Method

Recursion-tree method for finding the running time of a divide and conquer algorithm

COMP3010 - 6.0 - Divide and Conquer

Recurrence equation for divide and conquer algorithm

COMP3010 - 5.2 - Greedy Algorithm - Activity Selection

Worked example for activity selection problem

COMP3010 - 5.1 - Greedy Algorithm - Optimal Substructure

Constructing a greedy solution

COMP3010 - 5.0 - Greedy Algorithm

Introduction to greedy algorithm

COMP3010 - 4.3 - Developing a DP Algorithm - Part 2 - Recursive Relation

Writing the algorithm and code for rod-cutting

COMP3010 - 4.2 - Developing a DP Algorithm - Part 1 - Optimal Substructure

Identifying overlapping subproblems, optimal substructure, rod-cutting example

COMP3010 - 4.1 - Optimal Substructure

Understanding optimal substructure

COMP3010 - 4.0 - Overlapping Subproblems

Dynamic programming refresher, fibonacci, and LCSS

COMP3010 - 3.3 - Recursive Backtracking

Recursive backtracking and branch-and-bound

COMP3010 - 3.2 - Search Space

Generating the search space for brute force algorithm

COMP3010 - 3.1 - Permutations and Combinations

Short refresher on permutation and combination

COMP3010 - 3.0 - Brute Force Methods

General brute-forcing methods

COMP3010 - 2.3 - Loop Invariants

Revision of loop invariant topic from COMP2010/225

COMP3010 - 2.2 - Correctness of Recursive Algorithms

Using induction to show correctness of recursive algorithms

COMP3010 - 2.1 - Mathematical Induction

Revision on induction

COMP3010 - 2.0 - Correctness of Algorithms

Introduction on algorithm correctness

COMP3010 - 1.3 - Complexity Notation

Big-O notation, worst-case, best-case, average-case

COMP3010 - 1.2 - Complexity Analysis Introduction

Introduction to algorithm analysis, RAM model of computation

COMP3010 - 1.1 - Problems and Algorithms

Introduction to the unit

COMP3010 - 1.0 - Introduction

Introduction to the unit

COMP333 Algorithm Theory and Design - W13 2019 - Revision

Revision notes for Comp333

COMP333 Algorithm Theory and Design - W9 2019 - Graph Algorithms

Lecture notes for Week 9 of COMP333, 2019, Macquarie University

COMP333 Algorithm Theory and Design - W8 2019 - Probabilistic Algorithms

Lecture notes for Week 8 of COMP333, 2019, Macquarie University

COMP333 Algorithm Theory and Design - W7 2019 - Strings Algorithms

Lecture notes for Week 7 of COMP333, 2019, Macquarie University

COMP333 Algorithm Theory and Design - W6 2019 - Divide and Conquer

Lecture notes for Week 6 of COMP333, 2019, Macquarie University

COMP333 Algorithm Theory and Design - W5 2019 - Greedy Algorithm

Lecture notes for Week 5 of COMP333, 2019, Macquarie University

COMP333 Algorithm Theory and Design - W4 2019 - Dynamic Programming

Lecture notes for Week 4 of COMP333, 2019, Macquarie University

COMP333 Algorithm Theory and Design - W3 2019 - Exhaustive Search

Lecture notes for Week 3 of COMP333, 2019, Macquarie University