PPT-Sequential Learning

1 What is Sequential Learning 2 Topics from class Classification learning learn x y Linear naïve Bayes logistic regression Nonlinear neural nets trees Not quite classification learning. columbiaedu Department of Electrical Engineering Columbia Universit y New York NY 10027 USA Sanjiv Kumar sanjivkgooglecom Google Research New York NY 10011 USA ShihFu Chang sfchangeecolumbiacom Department of Electrical Engineering Columbia Universit columbiaedu Department of Electrical Engineering Columbia Universit y New York NY 10027 USA Sanjiv Kumar sanjivkgooglecom Google Research New York NY 10011 USA ShihFu Chang sfchangeecolumbiacom Department of Electrical Engineering Columbia Universit and Sequential Data Sequential Data •Often arise through measurement of time series •Snowfall measurements on successive days in Buffalo •Rainfall measurements in Chirrapunji •Dail A PRACTICAL APPROACH. Richard D. Courtright, Ph.D.. Gifted Education Research Specialist. Duke University Talent Identification Program. LEARNING STYLES DEFINED:. Style is the consistent, personal way. Loop Execution on . GPU and CPU. Mehrzad. . Samadi. 1. Amir Hormati. 2. Janghaeng. Lee. 1. and . Scott . Mahlke. 1. 1. 1. University . of Michigan - Ann . Arbor. 2. Microsoft Research, Microsoft. Amdahl’s Law. Lei Li. Computer Science Department. School of Computer Science . Carnegie Mellon University. leili@cs.cmu.edu. 1. School of Computer Science. . Efficient Parallel Learning of Linear Dynamical Systems on SMPs. How is this a predictor of your success in medical school and long- term as a physician?. Nancy B. Clark, M.Ed.. Director of Medical Informatics Education. Learning Styles and Approaches. 1. Learning Styles and Approaches. PSY505. Spring term, 2012. March 26, 2012. Today’s Class. Sequential Pattern Mining. Related to. Association Rule Mining. MOTIF Extraction. Similarities. MOTIF Extraction can be seen as a type of sequential pattern mining. Lecture 8. Hartmut Kaiser. hkaiser@cct.lsu.edu. http://www.cct.lsu.edu/˜. hkaiser. /spring_2015/csc1254.html. Programming Principle of the Day. Principle of least . astonishment (POLA/PLA). The . principle of least astonishment is usually referenced in regards to the user interface, but the same principle applies to written code. . Iterative Contraction and . Merging. Bayesian Sequential . Partitioning. JND-BSP. 1. Manifold Learning. Bosh Shih. 2. O. utline. Introduction. Principal Component Analysis (PCA. ). Linear Discriminant Analysis (LDA. Double - 1 Double - Blind Sequential Police Lineup Procedures: Toward an Integrated Laboratory & Field Practice Perspective Final Report Grant # 2004 - IJ - CX - 0044 March 31, 2007 Nancy K. Steblay Primer on Sequential Design Methods . and Design Choices. Ronan Fitzpatrick. Lead Statistician. nQuery. Webinar. Host. Agenda. Sequential Design Overview. Issues in Sequential Design. Group Sequential Design. Models and applications. Outline. Sequence Data. Recurrent Neural Networks Variants. Handling Long Term Dependencies. Attention Mechanisms. Properties of RNNs. Applications of RNNs. Hands-on LSTM-supported timeseries prediction. on Chest X-Rays. Matthew Beaubien, advised by Dr. . Lubomir. . Hadjiiski. and Dr. . Heang. -Ping Chan. Motivation. How do we train on a lot of data without sharing it?.