PPT-Classification and Prediction:

Ensemble Methods Bamshad Mobasher DePaul University Ensemble methods Use a combination of models to increase accuracy Combine a series of k learned models M 1 M 2 Mk with the aim of creating an improved model . Static Branch Prediction. Code around delayed branch. To reorder code around branches, need to predict branch statically when compile . Simplest scheme is to predict a branch as taken. Average misprediction = untaken branch frequency = 34% SPEC. Elad. . Hazan. (. Technion. ). Satyen Kale . (Yahoo! Labs). Shai. . Shalev-Shwartz. (Hebrew University). Three Prediction Problems: . I. Online Collaborative Filtering. Users: . {1, 2, …, m}. Movies: . Saehoon Kim. §. , . Yuxiong He. *. ,. . Seung-won Hwang. §. , . Sameh Elnikety. *. , . Seungjin Choi. §. §. *. Web Search Engine . Requirement. 2. Queries. High quality + Low latency. This talk focuses on how to achieve low latency without compromising the quality. Yongin. Kwon, . Sangmin. Lee, . Hayoon. Yi, . Donghyun. Kwon, . Seungjun. Yang, . Byung. -. Gon. Chun,. Ling Huang, . Petros. . Maniatis. , . Mayur. . Naik. , . Yunheung. . Paek. USENIX ATC’13. Research Interests/Needs. 1. Outline. Operational Prediction Branch research needs. Operational Monitoring Branch research needs. New experimental products at CPC. Background on CPC. Thanks to CICS/ESSIC/UMD for Inviting us . which method should I use? . (An introduction to ADME . WorkBench. ). May 7, 2013. Conrad Housand. chousand@aegistg.com. www.admewb.com. Framing the Question. Q: Which human PK prediction. method should I use?. Prediction is important for action selection. The problem:. prediction of future reward. The algorithm:. temporal difference learning. Neural implementation:. dopamine dependent learning in BG. A precise computational model of learning allows one to look in the brain for “hidden variables” postulated by the model. Emura. , Chen & Chen [ 2012, . PLoS. ONE 7(10) ] . Takeshi . Emura. (NCU). Joint work with Dr. Yi-. Hau. Chen and Dr. . Hsuan. -Yu Chen (. Sinica. ). 國立東華大學 應用數學系. 1. 2013/5/17. Matthew S. Gerber, Ph.D.. Assistant Professor. Department of Systems and Information Engineering. University of Virginia. IACA Presentations on Social Media. The Modern Analyst. and Social Media (Woodward). Presentation to AMS Board on Enterprise Communications. September 2012. ESPC Overview. Introduction. ESPC is an . interagency collaboration . between DoD (Navy, Air Force), NOAA, DoE, NASA, and NSF for coordination of research to operations for an earth system analysis and extended range prediction capability. . Daniel P. Eleuterio, . Office of Naval Research. Jessie Carman, NOAA Office of Ocean and Atmosphere Research. Fred . Toepfer. , NOAA National Weather Service. Dave . McCarren. , Naval Meteorology and Oceanography Command. Objectives. To better understand variability in eastern upwelling regions and the Gulf of Guinea. To enhance climate modelling and prediction capabilities. Improve understanding of marine ecosystems for better prediction and management. Wayne . Wakeland. Systems . Science . Seminar . Presenation. 10/9/15. 1. Assertion. Models . must, of course, be . well suited to their intended . application. Thus, . models . for evaluating . policies must be able to . Introduction, Overview. Classification using Graphs. Graph classification – Direct Product Kernel. Predictive Toxicology example dataset. Vertex classification – . Laplacian. Kernel. WEBKB example dataset.