PPT-A Scalable Bootstrap for Massive Data

Ariel Kleiner Ameet Talwalkar Purnamrita Sarkar Michael I Jordan Why bootstrap Made it possible to use computers not only to compute estimates but also to assess the quality of . Robin H. Lock, Burry Professor of Statistics. Patti Frazer Lock, Cummings Professor of Mathematics. St. Lawrence University. USCOTS 2011. Raleigh, NC. The Lock. 5. Team. Robin & Patti. St. Lawrence. Robin H. Lock. Burry Professor of Statistics. St. Lawrence University. rlock@stlawu.edu. Science Today. SUNY Oswego, March 31, 2010. Bootstrap CI’s & Randomization Tests. . (1) What are they?. Course Introduction. Mining of Massive Datasets. Jure Leskovec, . Anand. . Rajaraman. , Jeff Ullman . Stanford University. http://www.mmds.org . Note to other teachers and users of these . slides:. We . Robin Lock – St. Lawrence University. Patti Frazer Lock – St. Lawrence University. Kari Lock Morgan – Duke / Penn State. Eric F. Lock – Duke / U Minnesota. Dennis F. Lock – Iowa State / Miami Dolphins. Model Building in Econometrics. Parameterizing the model. Nonparametric analysis. Semiparametric analysis. Parametric analysis. Sharpness of inferences follows from the strength of the assumptions. A Model Relating (Log)Wage . Saharon Rosset. An abstract view of statistics. There is a “world” (=unknown distribution) F. We observe some data from the world, say 100 heights (z) and weights (y) of random people. . We want to learn about some property of the world F, e.g.:. Larry Weldon. Statistics and Actuarial Science. Simon Fraser University. Nov. 27, 2008. 1. Outline of Talk. Why simple techniques overlooked. Simplest kernel . estimation and smoothing. Simplest . multivariate data display. (Part 1). Allan Rossman, Cal Poly – San Luis Obispo. Robin Lock, St. Lawrence University. George Cobb (. TISE. , 2007). 2. “What . we teach is largely the technical machinery of numerical approximations based on the normal distribution and its many subsidiary cogs. This machinery was once necessary, because the conceptually simpler alternative based on permutations was computationally beyond our . Jen Kramer • . JS Summit • . November . 19, . 2013. Agenda. Grounding in mobile techniques. Background on responsive design. Introduce Bootstrap and Foundation. Compare Bootstrap and Foundation. Declare a winner!!!. api. /framework developed by Twitter for mobile first, . responsive. (. to changing devices it is displayed on. ) web sites/applications. . . (. api. of CSS, and . javascript. extensions). And - HTML . Larry Peterson. In collaboration with . Arizona. , Akamai. ,. . Internet2. , NSF. , North Carolina, . Open Networking Lab, Princeton. (and several pilot sites). S3. DropBox. GenBank. iPlant. Data Management Challenge. Based on “An . Introduction to the . Bootstrap”, . B. . Efron. and R. J. . Tibshirani. , . chapter 20. Aviv Navon. Intro. Suppose we are in the simple one-sample situation, having observed a random sample . bootstrap?. Documentation . Media Queries for responsiveness. Usage : Link or download?. Building a responsive web page using bootstrap. Modals: . . Gootstrap. . plug-ins for interactive dialog windows. . Ashvin Goel. Electrical and Computer Engineering. University of Toronto. ECE 1724, Winter 2021. Web-Scale Apps. Applications that are . hosted in massive-scale . computing infrastructures . such as data centers.