PPT-Lower Bounds for the Capture Time: Linear, Quadratic, and Beyond

How to catch a robber on a graph The game of Cops and Robbers The rules of the game The C op is placed f irst C The R obber may then choose a placement C R Next they alternate. Sx Qx Ru with 0 0 Lecture 6 Linear Quadratic Gaussian LQG Control ME233 63 brPage 3br LQ with noise and exactly known states solution via stochastic dynamic programming De64257ne cost to go Sx Qx Ru We look for the optima under control N with state input and process noise linear noise corrupted observations Cx t 0 N is output is measurement noise 8764N 0 X 8764N 0 W 8764N 0 V all independent Linear Quadratic Stochastic Control with Partial State Obser vation 102 br Shubhangi. . Saraf. Rutgers University. Based on joint works with . Albert Ai, . Zeev. . Dvir. , . Avi. . Wigderson. Sylvester-. Gallai. Theorem (1893). v. v. v. v. Suppose that every line through . How to catch a robber on a graph?. The game of Cops and Robbers. The rules of the game. The . C. op is placed . f. irst. C. The . R. obber may . then. choose a placement. C. R. Next, they . alternate. Regression. By, Tyler . Laufersweiler. Quadratic Regression. Title: Finding . the equation of curves throughout . life . using quadratic regression. This lesson uses a graphing calculator and Geometer’s Sketchpad to find the function of curves throughout the world. This hands-on lesson allows students to explore quadratic regression using their calculators (quadratic regression applet). Students will use Geometer’s Sketchpad to record data points and their calculators or a website to generate a quadratic function using the data that represents the curve. . Section 3.4 beginning on page 122. The Big Ideas. The . quadratic formula . allows us to . solve any quadratic equation . once it is written in standard form. The . discriminant. . is a part of the quadratic formula that tells us . Shubhangi. . Saraf. Rutgers University. Based on joint works with . Albert Ai, . Zeev. . Dvir. , . Avi. . Wigderson. Sylvester-. Gallai. Theorem (1893). v. v. v. v. Suppose that every line through . Perfect Square Trinomials. Examples. x. 2. + 6x + 9. x. 2. - 10x + 25. x. 2. + 12x + 36. Creating a Perfect . Square Trinomial. X. 2. . + 14x + ____ . Find the constant term by squaring half . Standards 8-10. Graphs of Quadratic Functions . U- Shaped Graph . Vertical y=x. 2. or Horizontal x=y. 2. Positive Negative . Summary: The of a Quadratic Function is U shaped. . Positve. Find the roots:. 1) x. 2. – 64 = 0 . 2) 8x. 2. – 64x = 0. 3) x. 2. – 16x + 64 = 0. 1) Ensure the quadratic equation is set to zero.. 2) Factor the quadratic equation (GCF, perfect square binomial [DOTS], trinomial). Searching. : Given a large set of distinct keys, preprocess them so searches can be performed as quickly as possible. 1. CS 840 Unit 1: Models, Lower Bounds and getting around Lower bounds. Searching. Steven J Miller, Williams College (sjm1@Williams.edu). 1. https://web.williams.edu/Mathematics/sjmiller/public_html/math/talks/talks.html. Goals. Learn how to solve polynomial equations and see applications of polynomials and ways to find their roots.. dynamic data structures. Shachar. Lovett. IAS. Ely . Porat. Bar-. Ilan. University. Synergies in lower bounds, June 2011. Information theoretic lower bounds. Information theory. is a powerful tool to prove lower bounds, e.g. in data structures. Dagstuhl Workshop. March/. 2023. Igor Carboni Oliveira. University of Warwick. 1. Join work with . Jiatu. Li (Tsinghua). 2. Context. Goals of . Complexity Theory. include . separating complexity classes.