PDF-DRUG TESTING WELFARE RECIPIENTS--FALSE POSITIVES, FALSE NEGATIVES,UNAN

Sheldon DanzigerHenry J Meyer Collegiate Professor of Social Work and Public Policy Director Center on Poverty Risk and Mental HealthUniversity of MichiganRukmalie JayakodyDevelopment and Family S. Lihi. . Zelnik. -Manor. lihi@ee.technion.ac.il. ROC. Precision-Recall. circles. Not. circles. Truth:. Result:. circles. Not. circles. Precision-Recall. circles. Not. circles. Truth:. Result:. circles. Reducing False Positives Without Increasing Regulatory Risk &#x/MCI; 2 ;&#x/MCI; 2 ;Introduction................................Achieving a Balance................................Match Keys Sheldon DanzigerHenry J. Meyer Collegiate Professor of Social Work and Public Policy, Director, Center on Poverty Risk and Mental HealthUniversity of Michigan.Rukmalie JayakodyDevelopment and Family S European Molecular Biology Laboratory. Predoc. Bioinformatics Course. 17. th. Nov 2009. Tim Massingham, tim.massingham@ebi.ac.uk. Motivation. Already come across several cases where need to correct . and . Negatives. 0. 1. 2. 3. 4. 5. -2. -1. -4. -3. Meet Pete. The Positive Pirate. Together, they’re called the “Positives”. Now meet their arch enemies…. Ned. The Negative Ninja. Together, they’re called the “Negatives”. CSE P 576. Larry Zitnick (. larryz@microsoft.com. ). Many slides courtesy of . Steve . Seitz. How do we describe an image patch?. How do we describe an image patch?. Patches with similar content should have similar descriptors.. and . Negatives. 0. 1. 2. 3. 4. 5. -2. -1. -4. -3. Meet Pete. The Positive Pirate. Together, they’re called the “Positives”. Now meet their arch enemies…. Ned. The Negative Ninja. Together, they’re called the “Negatives”. Robots and Brains. Who wants a robot to clean your house? . [Photo Credit: . iRobot. ]. Stanford STAIR Robot. [Credit: Ken Salisbury]. What’s missing?. Control . Perception . The software. Stanford autonomous helicopter. Presented by Gautam Sanka. Susan C. Weber, Henry Lowe, Amar Das, Todd Ferris. Introduction and Objectives. Challenges. Patient Privacy vs. Building Cross-Site records. Solutions. Mandate that identifiers be disclosed. Eamonn Keogh . eamonn@cs.ucr.edu. Quick Reminder. We saw the nearest neighbor algorithm.. As we saw that we could use any distance function…. Mantled Howler Monkey. Alouatta palliata. Red Howler Monkey . Marion . Oberhuber. . & Richard . Daws. .. Null Distribution of T. . The . Test Statistic T. . Computed at each . voxel. . S. ummarises . evidence about . H. 0. . Recap - . Hypothesis . Blessing of dimensionality. Gorban A.N. . Joint work with. . Tyukin . I.Y.,. University of Leicester. Plan. Geometrical preliminaries, from Gibbs to Levy. Motivation from machine learning. Stochastic separation theorems for . *. The Good, the Bad, and the Ugly. . Andy . Earle. Hewlett-Packard Enterprise. Security . Solutions Architect. Who am I?. Andy Earle. CISSP, CSSLP, CEH. HPE . Fortify. Application Security Solutions Architect / Presales Engineer. OUTLINE. Basic concepts and motivation. Extending the basic occupancy model: a building block for false positives . (Royle and Link 2006). The integrated model of Miller et al. (2011). In . unmarked .