PPT-Polynomial Approximation in

Handwriting Recognition Stephen M Watt University of Western Ontario International Workshop on SymbolicNumeric Computation SNC 2011 79 June 2011 San Jose California The Pen as an Input Device. . of Edit Distance. Robert Krauthgamer, . Weizmann Institute of Science. SPIRE 2013. TexPoint. fonts used in EMF. . Read the . TexPoint. manual before you delete this box. .: . A. A. A. A. A. A. A. Ankush Sharma . A0079739H. Xiao Liu . A0060004E. Tarek Ben Youssef A0093229. Reference. Terminologies – TSP & PTAS (Polynomial Time Approximation Schemes). Algorithm – A PTAS for Euclidian TSP (2D). Hui. Pan, . Yunfei. . Duan. possible problem in physical measurement . Sometimes know the value of a function f(x) at a set of points, but we don’t have an analytic expression for f(x) that lets us calculate its value at an arbitrary point. . 1. Tsvi. . Kopelowitz. Knapsack. Given: a set S of n objects with weights and values, and a weight bound:. w. 1. , w. 2. , …, w. n. , B (weights, weight bound).. v. 1. , v. 2. , …, v. n. (values - profit).. Alexander . Veniaminovich. IM. , . room. . 3. 44. Friday. 1. 7. :00. or. Saturday 14:30. Approximation. . algorithms. . 2. We will study. . NP. -. hard optimization problem. 3. What you should know. 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 2014/2015. Hans L. . Bodlaender. Johan M. M. van Rooij. C-approximation. Optimization problem: output has a value that we want to . maximize . or . minimize. An algorithm A is an . 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. . Now, use the reciprocal function and tangent line to get an approximation.. Lecture 31 – . Approximating Functions. 1. 1. 2. 3. 2. 2. 2.01. First derivative gave us more information about the function (in particular, the direction).. 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. Planar Curve Offset. Based on Circle . Approximation. Curve Offset. Planar Curve . Offset Based . on Circle . Approximation – Lee, Kim, . Elber. .. Concept. Circle Approximation. Offset Approximation. Stochastic . Optimization. Anupam Gupta. Carnegie Mellon University. IPCO Summer . School. Approximation . Algorithms for. Multi-Stage Stochastic Optimization. {vertex cover, . S. teiner tree, MSTs}. 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.