PPT-CS6045: Advanced Algorithms

Data Structures RedBlack Trees Redblack trees A variation of binary search trees Operations designed to guarantee that the height h O lg n Redblack trees properties Every . Rahul. . Santhanam. University of Edinburgh. Plan of the Talk. Preliminaries and Motivation. Informational Bottlenecks: Proof Complexity and Related Models. Computational Bottlenecks: OPP and Compression. Hazem Ali, Borislav Nikoli. ć,. Kostiantyn Berezovskyi, Ricardo Garibay Martinez, Muhammad Ali Awan. Outline. Introduction. Non-Population Metaheuristics. Population Metaheuristics. Genetic Algorithims (GA). Some of the fastest known algorithms for certain tasks rely on chance. Stochastic/Randomized Algorithms. Two common variations. Monte Carlo. Las Vegas. We have already encountered some of both in this class. Lecture 18. The basics of graphs.. 8/25/2009. 1. ALG0183 Algorithms & Data Structures by Dr Andy Brooks. Watch out for self-loops in graphs.. 8/25/2009. ALG0183 Algorithms & Data Structures by Dr Andy Brooks. Chapter 4. Local search algorithms. Hill-climbing search. Simulated annealing search. Local beam search. Genetic algorithms. Outline. In many optimization problems, the . path. to the goal is irrelevant; the goal state itself is the . Describing what you know. Contents. What are they and were do we find them?. Why show the algorithm?. What formalisms are used for presenting algorithms?. Notes on notation. Algorithmic performance. Where do we find them. Optimization problems, Greedy Algorithms, Optimal Substructure and Greedy choice. Learning & Development Team. http://academy.telerik.com. . Telerik Software Academy. Table of Contents. Optimization Problems. Lecture 13. Bubble Sort. 8/25/2009. 1. ALG0183 Algorithms & Data Structures by Dr Andy Brooks. comparison . sort. worse-case, average case O(N. 2. ). best-case O(N. ). (recognise no swaps). in-place. Annie . Yang and Martin Burtscher*. Department of Computer Science. Highlights. MPC compression algorithm. Brand-new . lossless . compression algorithm for single- and double-precision floating-point data. Keyang. He. Discrete Mathematics. Basic Concepts. Algorithm . – . a . specific set of instructions for carrying out a procedure or solving a problem, usually with the requirement that the procedure terminate at some point. BIT 1003- Presentation 4. An algorithm is a method for solving a class of problems. . While computer scientists think a lot about algorithms, the term applies to any method of solving a particular type of problem. . 1. Evolutionary Algorithms. CS 478 - Evolutionary Algorithms. 2. Evolutionary Computation/Algorithms. Genetic Algorithms. Simulate “natural” evolution of structures via selection and reproduction, based on performance (fitness). Raman Veerappan. EPS 109 Final Project. Introduction. Goals. To examine various maze solving algorithms using MATLAB determine which algorithms are most effective for which mazes. Two main algorithms examined. 1. Decrease-and-Conquer. Reduce . original problem . instance to . smaller . instance . of the same problem. Solve smaller . instance. Extend solution . of smaller . instance . to obtain solution to original instance.