'M step' presentation slideshows

MAD-Bayes: MAP-based Asymptotic Derivations from Bayes

MAD-Bayes: MAP-based Asymptotic Derivations from Bayes. Michael I. Jordan INRIA University of California, Berkeley. May 11, 2013. Acknowledgments : Brian Kulis , Tamara Broderick. Statistical Inference and Big Data.

841 views • 66 slides

Expectation-Maximization (EM) Algorithm

1.66k views • 37 slides

Chapter 2: Basics from Probability Theory and Statistics

Chapter 2: Basics from Probability Theory and Statistics. 2.1 Probability Theory Events, Probabilities, Random Variables, Distributions, Moments Generating Functions, Deviation Bounds, Limit Theorems Basics from Information Theory 2.2 Statistical Inference: Sampling and Estimation

927 views • 35 slides

Deterministic Annealing and Robust Scalable Data mining for the Data Deluge

Deterministic Annealing and Robust Scalable Data mining for the Data Deluge . Petascale Data Analytics: Challenges, and Opportunities (PDAC-11 ) Workshop at SC11 Seattle November 14 2011. Geoffrey Fox gcf@indiana.edu http://www.infomall.org http://www.futuregrid.org

494 views • 33 slides

Top-Down and Bottom-Up Scheduling in Swarm

668 views • 27 slides

Splash Screen

Splash Screen. Chapter 5. Lesson 5-2. (over Chapter 4). The U.S. Bank Tower in Los Angeles, California, is 1,018 feet tall. About how many meters tall is the building?. A B C D. Use the conversion factor: 1 foot = 0.305 meters. A. 31 m B. 290 m C. 310 m D. 3,338 m.

350 views • 26 slides

Compositions of Transformations

346 views • 23 slides

Lecture No. 16

Lecture No. 16. Drawing SFD and BMD. Objective:. To be able to drawn SFD and BMD using summation method. Notes To Remember When Drawing SFD and BMD. The change of shear between two points A and B is equal to the area of the loading between A and B.

188 views • 10 slides