PDF-An Optimal Algorithm for the Distinct Elements Problem

Kane Harvard University One Oxford Street Cambridge MA 02138 dankanemathharvardedu Jelani Nelson MIT CSAIL 32 Vassar Street Cambridge MA 02139 minilekmitedu David P Woodruff IBM Almaden Research Center 650 Harry Road San Jose CA 95120 dpwoodruusibmc.  . Given a stream . , where . , count the number of distinct items (so we are in the cash register model). Example: 3 5 7 4 3 4 3 4 7 5 9. 5 distinct elements: 3 4 5 7 9 (we only want the count of distinct elements, and not the set of distinct elements). CIS 606. Spring 2010. Greedy Algorithms. Similar to dynamic programming.. Used for optimization problems.. Idea. When we have a choice to make, make the one that looks best . right now. . Make . a locally . Lecture 10. Fang Yu. Department of Management Information Systems. National . Chengchi. University. Fall 2010. Fundamental Algorithms. Brute force, Greedy, Dynamic Programming:. Matrix Chain-Products . Xiaohua. Li and . Jeong. . Kyun. Lee. Department of Electrical and Computer Engineering . State University of New York at Binghamton . {xli,jlee54}@binghamton.edu . Major contributions. Develop efficient algorithm to construct optimal multi-hop path in arbitrarily large wireless networks. , Convexity, and the quest towards Optimal Algorithms. Boaz Barak. Harvard University. Microsoft Research. Partially based on work in progress with . Sam Hopkins. , . Jon Kelner, . Pravesh Kothari. , Ankur Moitra and Aaron Potechin.. Chris . Seto. Andrea Smith. Problem description. Given a list of a cities and distance between each pair of cities, what is the shortest possible route that visits each?. NP-hard problem. Problem usually modeled as an undirected graph. Abhilasha Seth. CSCE 669. Replacement Paths. G = (V,E) - directed graph with positive edge weights. ‘s’, ‘t’ - specified vertices. π. (s, t) - shortest path between them. Replacement Paths:. A computer algorithm is. a detailed step-by-step method for. solving a problem. by using a computer.. Problem-Solving (Science and Engineering). Analysis. How does it work?. Breaking a system down to known components. like me to cover on . Thursday. Asymptotic Notation. Binary. Search. T(n)=T(n/2) O(1). O(log. n). Merge Sort. T(n)=2T(n/2) O(n). O(n log n). Towers of Hanoi. T(n)=2T(n-1) O(1). O(2. n. ). Integer. Multiplication (. Keith Dalbey, Ph.D.. Sandia National Labs, Dept 1441, Optimization and Uncertainty Quantification. Michael Levy, Ph.D.. Sandia National Labs, Dept 1442, Numerical Analysis and Applications. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94AL85000.. Rohit. Ray. ESE 251. The goal of the . Traveling. Salesman Problem (TSP) is to find the most economical way to tour of a select number of “cities” with the following restrictions:. You must visit each city once and only once. Greedy algorithms, coin changing problem. Haidong. . Xue. Summer 2012, at GSU. What is a greedy algorithm?. Greedy algorithm. : “an algorithm always makes the choice that looks best at the moment”. Announcements. I am not Prof. Rubinstein. He will be back next week. My name is Mary Wootters. New HW posted today!. Roadmap. Sorting. Graphs!. Longest, Shortest, Max and Min. …. Data structures. Asymptotic Analysis. . SYFTET. Göteborgs universitet ska skapa en modern, lättanvänd och . effektiv webbmiljö med fokus på användarnas förväntningar.. 1. ETT UNIVERSITET – EN GEMENSAM WEBB. Innehåll som är intressant för de prioriterade målgrupperna samlas på ett ställe till exempel:.