PPT-False Positives in Static Analysis

The Good the Bad and the Ugly Andy Earle HewlettPackard Enterprise Security Solutions Architect Who am I Andy Earle CISSP CSSLP CEH HPE Fortify Application Security Solutions Architect Presales Engineer. 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 . Morphometry. Methods for Dummies 2013. Elin. Rees & Peter . McColgan. Contents. General idea. Pre-Processing. Spatial normalisation. Segmentation. Modulation. Smoothing. Statistical analysis. GLM. Oleg . Girko. , Alexey Lastovetsky. School of Computer Science & Informatics. University College Dublin. Dublin, Ireland. GridRPC and collective mapping. GridRPC limitations. Individual mapping. Client-server communication only. 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.. Bryce Boe. 2013/03/07. University of California Santa Barbara. Bryce Boe, Charlotte Hill, Michelle Len, Greg Dreschler, Phillip Conrad, Diana Franklin. Motivation. Scratch project assessment. is tedious and error prone. 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 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. 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 . Claire Le Goues. 2015 (c) C. Le Goues. 1. Learning goals. Really understand control- and data-flow analysis.. Receive a high-level introduction to more formal proving tools.. Develop evidence-based recommendations for how to deploy analysis tools in your project or organization.. 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 .