PPT-Area Approximation

4B Exact Area Use geometric shapes such as rectangles circles trapezoids triangles etc rectangle triangle parallelogram Approximate Area Midpoint. 125 Bleed print area will be cut away 6pp back cover area 6pp front cover area 6pp middle area middle front area inside back cover area inside front cover area 14125 4625 14375 475 50 CD Jewel Case Inse 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. . 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. Differentials and Linear Approximation. BC Calculus. Related Rates :. How . fast . is . y . changing as . x . is changing?. -. Differentials:. How . much. does . y . change as . x . changes?. for two geometric problems. Yi Wu. IBM Almaden Research. Based on joint work with. Venkatesan. . Guruswami. . Prasad . Raghavendra. . Rishi . Saket. . . CMU. . Anupam. Gupta. Carnegie Mellon University. stochastic optimization. Question: . How to model uncertainty in the inputs?. data may not yet be available. obtaining exact data is difficult/expensive/time-consuming. 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).. 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). Peter Andras. School of Computing and Mathematics. Keele University. p.andras@keele.ac.uk. Overview. High-dimensional functions and low-dimensional manifolds. Manifold mapping. Function approximation over low-dimensional projections. 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. *University . of California . Berkeley. Mohsen Imani, . Abbas . Rahimi. *. , . Tajana S. Rosing. Resistive Configurable Associative Memory . for Approximate . Computing. Motivation. 2. Internet of Things. Grigory. . Yaroslavtsev. . Penn State + AT&T Labs - Research (intern). Joint work with . Berman (PSU). , . Bhattacharyya (MIT). , . Makarychev. (IBM). , . Raskhodnikova. (PSU). Directed. Spanner Problem. 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 . Chapter 5.5. Linear Approximation. A useful characteristic of the tangent line to a curve at a point is that, for . -values near the point, the curve is approximately linear. In fact, the function values of the curve are approximated by the derivative values near the point of tangency.