PPT-Online Algorithms, Linear Programming, and the k-Server Pro

Seffi Naor Computer Science Dept Technion Approximation Algorithms T he Last Decade and The Next Princeton June 2011 Joint work with Nikhil Bansal Niv. Instructor: Wendy . Myrvold. E-mail: . wendym@csc.UVic.ca. Home page: . http://webhome.cs.uvic.ca/~wendym/445.html. Office hours: TBA, I have time for questions after class.. 2. About me:. M.Sc. : Computer Science, McGill University, 1983. 1. 3.3 Implementation. (1) naive implementation. (2) revised simplex method. (3) full tableau implementation. (1) Naive implementation :. Given basis . . Compute . ( solve . ). Choose . such that . Linear Programming. n . real-. valued. variables, . x. 1. , . x. 2. , . … . , . x. n. .. Linear . objective. . function. .. Linear . (in). equality. . constraints. .. Solvable in . polynomial time. Seffi. . Naor. Computer Science Dept.. Technion. . Barriers in Computational Complexity II Workshop 8/2010. Joint papers: Nikhil . Bansal. , . Niv. . Buchbinder. , . Kamal. Jain. Online Algorithms / Competitive Analysis. Another "Sledgehammer" in our toolkit. Many problems fit into the Linear Programming approach. These are optimization tasks where both the constraints and the objective are linear functions. Given a set of variables we want to assign real values to them such that they. Amrinder Arora. Permalink: http://standardwisdom.com/softwarejournal/presentations/. Summary. Online algorithms show up in . many. practical problems.. Even if you are considering an offline problem, consider what would be the online version of that problem.. Chapter 3: Introduction to Linear Programming. 2. Linear Programming. In order to solve OR problems, we need to turn a real-world problem into a mathematical model.. One of the most important models (due to its usefulness in solving a variety of problems) is the . INdia. Under NMEICT, MHRD. http://. nptel.ac.in. NPTEL Online Certification (NOC). Open Online Course (Enrollment . is free). https://onlinecourses.nptel.ac.in. Proctored Exam(optional for a fee). cities across the country. Introduction to Linear Programming. Introduction. Linear programming. Programming means planning. Model contains linear mathematical functions . An application of linear programming. Allocating limited resources among competing activities in the best possible way. Programming - Purpose, structure and the outline of a program.. An overview – programming is: . analysis of a scenario/problem. defining a specification. identifying input, process and output testing/debugging.. How would we formulate this as a linear program?. Announcements. Assignments:. HW4 (written). Due Tue 2/12, 10 pm. P2: Optimization. Released after lecture. Due Thu 2/21, 10 pm. Midterm 1 Exam. Mon 2/18, in class. Spring . 2018. Sungsoo. Park. Linear Programming 2018. 2. Instructor . Sungsoo. Park (room 4112, . sspark@kaist.ac.kr. , . tel:3121. ). Office hour: Mon, Wed 14:30 – 16:30 or by appointment. Classroom: E2-2 room 1120. understand and implement editorial opportunities and stunts across syndicated channels Monitor competitive programming and marketplace trends and analyze their implications Jim . Demmel. EECS & Math Departments. UC Berkeley. Why avoid communication? . Communication = moving data. Between level of memory hierarchy. Between processors over a network. Running time of an algorithm is sum of 3 terms:.