PPT-Scalable Statistical

Relational Learning for NLP William Y Wang William W Cohen Machine Learning Dept and Language Technologies Inst joint work with Kathryn Rivard Mazaitis Outline Motivation. brPage 1br Statistical Rejection of Bad Data Chauvenets Criterion statistical Chauvenets criterion brPage 2br once Example 4 SOLUTION Databank and Dissemination, . Central Statistics Office, Cork, Ireland. Eoin. . MacCuirc. . eoin.mccuirc@cso.ie. (00 353 21) 453 5504. Educational outreach fundamental to achieving strategic goals. Experiences from the Australian Bureau of Statistics (ABS). Trevor Sutton. 1. Outline. “Industrialisation” and the need for a strategic focus on statistical business processes. Introduction to GSBPM as a reference model . An Overview. Presented by Sterling . Chadee. 5. th. -6. th. November 2013. MISSION. The mission of the Central Statistical Office of Trinidad and Tobago is to facilitate informed decision-making, through the timely provision of a quality, relevant, user-oriented and dynamic statistical service, coordinating statistical activities and promoting the adherence to statistical standards.. Commutativity. Rule: Designing Scalable Software for Multicore Processors. Austin T. Clements, M. . Frans. . Kaashoek. , . Nickolai. . Zeldovich. , Robert T. Morris, and Eddie Kohler. MIT CSAIL and Harvard University. Processors. Presented by . Remzi. Can . Aksoy. *Some slides . are. . borrowed from a ‘Papers We Love’ . Presentation. EECS 582 – F16. 1. Outline. The . Scalable Commutativity Rule: . Whenever interface operations commute, they can be implemented in a way that scales. CESS 2016 – Session C3 ". Timely. . estimates. of . economic. . indicators. ". Ingo Kuhnert. European. Commission. DG . Economic. and Financial . Affairs. How statisticians see timeliness. <Picture>. Amy Kirkwood. Statistician. CR UK and UCL Cancer Trials Centre. IMMPACT-XVIII June 4. th. 2015 Washington DC. Central Statistical Monitoring in Clinical Trials. The ideas behind central statistical monitoring (CSM). John M. . Abowd. Associate Director for Research and Methodology and Chief Scientist, . U.S. . Census . Bureau. NAS Roundtable on Data Science. Meeting 1. Keck Center December 14, 2016. Acknowledgments and Disclaimer. Class 1. Tony Cox. tcoxdenver@aol.com. . University of Colorado at Denver. January 17, 2017. Proposed agenda. Introduction: Views on statistical consulting. Learning objectives. Course administration, grading, policies. 2011/2012. M. de Gunst. Lecture. 7. Statistical Data Analysis. 2. Statistical Data Analysis: Introduction. Topics. Summarizing data. Exploring . distributions . Bootstrap . Robust methods. Nonparametric tests (continued). 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. MURI Project: University of California, Irvine. Project Meeting. August 25. th. 2009. . Principal Investigator: Padhraic Smyth . . Goals for Today’s Meeting. Introductions and brief review of our project. COS 418: Distributed Systems. Lecture . 14. Wyatt Lloyd. Consistency Hierarchy. Linearizability. Sequential Consistency. Causal+ Consistency. Eventual Consistency. e.g., RAFT. e.g., Bayou. e.g., Dynamo.