PPT-Software Bug Localization with Markov Logic

Sai Zhang Congle Zhang University of Washington Presented by Todd Schiller Software bug localization finding the likely buggy code fragments A software system source code. Parag. . Singla. Dept. of Computer Science and Engineering. Indian Institute of Technology, Delhi. Joint work with people at . University of Washington and IIT Delhi . Overview. Motivation. Markov logic. Hao. Wu. Mariyam. Khalid. Motivation. Motivation. How would we model this scenario?. Motivation. How would we model this scenario?. Logical Approach. Motivation. How would we model this scenario?. Logical Approach. Logic and Probability. Parag Singla. Dept. of Computer Science & Engineering. Indian Institute of Technology Delhi. Overview. Motivation & Background. Markov logic. Inference & Learning. Abductive. Model Definition. Comparison to Bayes Nets. Inference techniques. Learning Techniques. A. B. C. D. Qn. : What is the. . most likely. . configuration of A&B?. Factor says a=b=0. But, marginal says. TO EVALUATE COST-EFFECTIVENESS. OF CERVICAL CANCER TREATMENTS. Un modelo de . Markov. en un árbol de . decisión para . un análisis . del . coste-efectividad . del tratamientos . de cáncer de cuello uterino. "Teaching the Speakers: Heritage Language Learners and the Classroom". Lonny Harrison. Texas Language Center . Center for Russian, East European, and Eurasian Studies. The University of Texas at Austin. Fehringer. Seminar: Probabilistic Models for Information Extraction. by Dr. Martin . Theobald. and Maximilian . Dylla. . Based on Richards, M., and . Domingos. , P. (2006). Markov Logic Networks. 1. Patrick Lazar, . Tausif. . Shaikh. , Johanna Thomas, . Kaleel. . Mahmood. . University of Connecticut . Department of Electrical Engineering. Outline. Objective. Range Test. Asynchronous . Test. GUI. Mose. Wahlstrom. Lattice Research & Development Team. May 16, 2014. Overview. Mose. Wahlstrom, BSEE OSU 1992. At Lattice for last 22 years. Excited to enhance partnership between Lattice and OSU. Parag. . Singla. & Raymond J. Mooney. Dept. of Computer Science. University of Texas, Austin. Motivation . [ Blaylock & Allen 2005] . Road Blocked!. Road Blocked!. Heavy Snow; Hazardous Driving. for the IoT. Nirupam Roy. M-W 2:00-3:15pm. CHM 1224. CMSC 715 : Fall 2021. Lecture . 3.1: Machine Learning for IoT. Happy or sad?. Happy or sad?. Happy or sad?. Happy or sad?. Past experience. P (. The dolphin is happy. The Internet is a constantly growing phenomenon, with lots of new websites launched every day. Patrick Bong. LBNL Interlock SME. Introduction. The BELLA Terra-Watt interlock upgrade . Expanded the number of lasers used in the LPA to a primary beam and a secondary beam. Added a new laser bay. Eliminated the relay based interlock system . in Markov Logic using an RDBMS. Feng . Niu. , Chris . Ré. , . AnHai. Doan, and Jude . Shavlik. University of Wisconsin-Madison. One Slide Summary. 2. Machine Reading . is a DARPA program to capture knowledge expressed in free-form text.