'Convex combination' presentation slideshows

Fair Share Scheduling

749 views • 49 slides

Logic-Based Methods for Global Optimization

Logic-Based Methods for Global Optimization. J. N. Hooker Carnegie Mellon University, USA November 2003. Basic Idea Assume the problem becomes convex when certain variables are fixed.

584 views • 45 slides

CS430 Computer Graphics

CS430 Computer Graphics. Color Theory. Topics. Colors CIE Color Model RGB Color Model CMY Color Model YIQ Color Model Intuitive Color Concepts HSV Color Model HLS Color Model. Colors. Colors A narrow frequency band within the electromagnetic spectrum. Colors. Visible band

833 views • 37 slides

CS 445/645 Fall 2001

496 views • 33 slides

Affine Transformations

Affine Transformations. Logistics. Required reading: Watt, Section 1.1. Further reading: Foley, et al, Chapter 5.1-5.5. David F. Rogers and J. Alan Adams, Mathematical Elements for Computer Graphics , 2 nd Ed., McGraw-Hill, New York, 1990, Chapter 2. Logistics: HW #1 handed out today

526 views • 33 slides

Uniprocessor scheduling

Uniprocessor scheduling. B.Ramamurthy. CSE421. Introduction. An important aspect of multiprogramming is scheduling. The resources that are scheduled are IO and processors. The goal is to achieve High processor utilization High throughput number of processes completed per unit time

427 views • 30 slides

Random Number Generators

Random Number Generators. Why do we need random variables?. random components in simulation ? need for a method which generates numbers that are random examples interarrival times service times demand sizes. terminology. Random Numbers

468 views • 30 slides

Totally Unimodular Matrices

Totally Unimodular Matrices. Simplex Algorithm . Elliposid Algorithm. Lecture 11: Feb 23. Integer Linear programs . Method: model a combinatorial problem as a linear program. Goal: To prove that the linear program has an integer optimum solution for every objective function.

960 views • 29 slides

Lecture 14 Simplex, Hyper-Cube, Convex Hull and their Volumes

Lecture 14 Simplex, Hyper-Cube, Convex Hull and their Volumes. Shang-Hua Teng. Linear Combination and Subspaces in m-D. Linear combination of v 1 (line) { c v 1 : c is a real number} Linear combination of v 1 and v 2 (plane) { c 1 v 1 + c 2 v 2 : c 1 ,c 2 are real numbers}

411 views • 28 slides

CS559: Computer Graphics

CS559: Computer Graphics. Lecture 14: More on Curves Li Zhang Spring 2010. Catmull-Rom Cubics. Catmull-Rom Cubic Curves. Demo http://www.cse.unsw.edu.au/~lambert/splines/CatmullRom.html n control points define n-2 segments Changing 1 point affects neighboring 4 segments. Cardinal Cubics.

287 views • 28 slides

Hidden Variables as Fruitful Dead Ends

Hidden Variables as Fruitful Dead Ends. Scott Aaronson (MIT). WWJPD?.

371 views • 27 slides

Geometry and Theory of LP

Geometry and Theory of LP. Standard (Inequality) Primal Problem: Dual Problem:. Geometry of the Prototype Example. P2. Max 3 P1 + 5 P2 s.t. P1 + < 4 (Plant 1) 2 P2 < 12 (Plant 2) 3 P1 + 2 P2 < 18 (Plant 3)

440 views • 26 slides

Mesh Parametrization with Butterfly Subdivision Scheme

Mesh Parametrization with Butterfly Subdivision Scheme. CGIV, 26~29 July 2004, Penang, Malaysia. Graduate School of Software Dongseo University, Busan, Korea Byung Gook Lee and Chung Jae Lim Nam Woo Kim, d5302010@dongseo.ac.kr. Abstract.

363 views • 16 slides

Computational Geometry (35/33)

268 views • 11 slides

Convex Combinations

193 views • 6 slides