PDF-Second Approximation

area A 2 A 212 r ProofIn the figure below observe that 21 a It is also evident from the green sin 2Therefore upon substituting from into Area 21a b sin 8 2 A . University of Washington. Adrian Sampson, . Hadi. Esmaelizadeh,. 1. Michael . Ringenburg. , . Reneé. St. Amant,. 2. . Luis . Ceze. , . Dan Grossman. , Mark . Oskin. , Karin Strauss,. 3. and Doug Burger. Actual area under curve:. Left-hand rectangular approximation:. Approximate area:. (too low). Approximate area:. Right-hand rectangular approximation:. (too high). Averaging the two:. 1.25% error. (too high). Sometimes we can handle NP problems with polynomial time algorithms which are guaranteed to return a solution within some specific bound of the optimal solution. within a constant . c. . of the optimal. Algorithms. and Networks 2015/2016. Hans L. . Bodlaender. Johan M. M. van Rooij. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . A. A. A. A. A. A. A. A. A. A. What to do if a problem is. Problems. Proofs. Approximations. Decision Problems. Given Some Universal Set X,. Let R be a subset of X.. The decision problem for R is:. Given an arbitrary element a of X, does. a belong to R?. Note: X is usually assumed to be a set of . Reuven. Bar-. Yehuda. . Gleb. . Polevoy. Dror. . Rawitz. . . Technion. 1. Multiple interference. 2. . w. e can . approximate. to . . For small interferences. Interval selection with multiple interference. A Mini-Survey. Chandra . Chekuri. Univ. of Illinois, Urbana-Champaign. Submodular Set Functions. A function . f. : 2. N. . . . R . is submodular if. . f(A. ) + . f(B. ) ≥ . f(A. . B. ) + . Problem. Yan Lu. 2011-04-26. Klaus Jansen SODA 2009. CPSC669 Term Project—Paper Reading. 1. Problem Definition. 2. Approximation Scheme. 2.1 Instances with similar capacities. 2.2 General cases . Outline. δ. -Timeliness. Carole . Delporte-Gallet. , . LIAFA . UMR 7089. , Paris VII. Stéphane Devismes. , VERIMAG UMR 5104, Grenoble I. Hugues Fauconnier. , . LIAFA . UMR 7089. , Paris VII. LIAFA. Motivation. How accurate is your estimate?. Differential Notation. The Linear Approximation to . y. = . f. (. x. ) is often written using the “differentials” . dx. and . dy. . In this notation, . dx. is used instead of . Dr. . Tayab . Din Memon. . Assistant Professor . Dept of Electronic Engineering, MUET, Jamshoro. . ACTIVE FILTERS and its applications . Objectives . Discuss about the Active filters, . its use and applications. . Stochastic . Optimization. Anupam Gupta. Carnegie Mellon University. IPCO Summer . School. Approximation . Algorithms for. Multi-Stage Stochastic Optimization. {vertex cover, . S. teiner tree, MSTs}. EECT 7327 . Fall 2014. Successive Approximation. (SA) ADC. Successive Approximation ADC. – . 2. –. Data Converters Successive Approximation ADC Professor Y. Chiu. EECT 7327 . Fall 2014. Binary search algorithm → N*. When the best just isn’t possible. Jeff Chastine. Approximation Algorithms. Some NP-Complete problems are too important to ignore. Approaches:. If input small, run it anyway. Consider special cases that may run in polynomial time.