PPT-Optimization: Algorithms

and Applications David Crandall Geoffrey Fox Indiana University Bloomington SPIDAL Video Presentation April 7 2017 Both PathologyRemote sensing working on 2D moving to 3D images Each pathology image could have 10 billion pixels and we may extract a million spatial objects per image and 100 million features dozens to 100 features per object per image We often tile the image into 4K x 4K tiles for processing We develop bufferingbased tiling to handle boundarycrossing objects For each typical study we may have hundreds to thousands of pathology images. TVCG 2013. Sungkil. Lee, Mike Sips, and Hans-Peter Seidel. Introduction. Class Visibility. Optimization . Example. Conclusion. Outline. Principles of effective color palettes (Trumbo, 1981) . Order: colors chosen to present an ordered statistical variables should be perceived as preserving that order. . CSE 8330. Instructor: . Dr.Margaret. H. Dunham. Presenter: . Akshaya. . Aradhya. Introduction. Query optimization in XML databases. Query optimization in Parallel databases. Comparison. Conclusion and Future work. for Geometry Processing. Justin Solomon. Princeton University. David . Bommes. RWTH Aachen University. This Morning’s Focus. Optimization.. Synonym(-. ish. ):. . Variational. methods.. This Morning’s Focus. Jonathan Hollingshead. Terms used in this presentation. Web page or page – a single document . on the Internet, typically with a single topic. Web site or site – a collection of individual web pages interconnected by hyperlinks. Optimization methods help us find solutions to problems where we seek to find the best of something.. This lecture is about how we formulate the problem mathematically.. In this lecture we make the assumption that we have choices and that we can attach numerical values to the ‘goodness’ of each alternative.. Collin . Bezrouk. 2-24-2015. Discussion Reference. Some of this material comes from . Spacecraft Trajectory Optimization. (Ch. 7) by Bruce Conway.. Optimization Problem Setup. Optimization problems require the following:. Silicon Photonic . NoCs. in Many-core Systems. Ayse. K. Coskun. 3. , . Anjun. Gu. 1. , Warren Jin. 4. , Ajay Joshi. 3. , Andrew B. Kahng. 1,2. , . Jonathan Klamkin. 4. , . Yenai. Ma. 3. , John Recchio. Presented by. : . Samia. . Abid. Student: MS(CS). Supervised by: Dr. . Nadeem. . Javaid. Associate Professor, Department of Computer Science, . COMSATS Institute of Information . Technology, 44000, Islamabad, Pakistan.. Qifeng. Chen. Stanford University. Vladlen. . Koltun. Intel Labs. Optical flow. Motion field between two image frames. Optical flow. Motion field between two image frames. Image 1. Image 2. optical flow. Applications. Lecture 5. : Sparse optimization. Zhu Han. University of Houston. Thanks Dr. . Shaohua. Qin’s efforts on slides. 1. Outline (chapter 4). Sparse optimization models. Classic solvers and omitted solvers (BSUM and ADMM). Classification of algorithms. The DIRECT algorithm. Divided rectangles. Exploration and Exploitation as bi-objective optimization. Application to High Speed Civil Transport. Global optimization issues. 10 Bat Algorithms Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, 2014 The bat algorithm (BA) is a bio-inspired algorithm developed by Xin-She Yang in 2010. 10.1 Echolocation of Bats Additive manufacturing (AM) is expanding the range of designable geometries, but to exploit this evolving design space new methods are required to find optimum solutions. Finite element based topology Michael Kantor. CEO and Founder . Promotion Optimization Institute (POI). First Name. Last Name. Company. Title. Denny. Belcastro. Kimberly-Clark. VP Industry Affairs. Pam. Brown. Del Monte. Director, IT Governance & PMO.