PPT-Probabilistic Model Checking of Systems with a Large State

Shoupon Lin Advisor Nicholas F Maxemchuk Department of Electrical Engineering Columbia University New York NY 10027 Problem Markov decision process or Markov chain with exceedingly large state space. Component-Based Shape Synthesis. Evangelos. . Kalogerakis. , . Siddhartha . Chaudhuri. , . Daphne . Koller. , . Vladlen. . Koltun. Stanford . University. Goal: generative model of shape. Goal: generative model of shape. (goal-oriented). Action. Probabilistic. Outcome. Time 1. Time 2. Goal State. 1. Action. State. Maximize Goal Achievement. Dead End. A1. A2. I. A1. A2. A1. A2. A1. A2. A1. A2. Left Outcomes are more likely. a Probabilistic . Lexical . Inference System. . Eyal Shnarch. ,. . Ido . Dagan, Jacob . Goldberger. PLIS - Probabilistic Lexical Inference System. 1. /34. The . entire talk in a single sentence. Ashish Srivastava. Harshil Pathak. Introduction to Probabilistic Automaton. Deterministic Probabilistic Finite Automata. Probabilistic Finite Automaton. Probably Approximately Correct (PAC) learnability. Chapter 1: An Overview of Probabilistic Data Management. 2. Objectives. In this chapter, you will:. Get to know what uncertain data look like. Explore causes of uncertain data in different applications. Indranil Gupta. Associate Professor. Dept. of Computer Science, University of Illinois at Urbana-Champaign. Joint work with . Muntasir. . Raihan. . Rahman. , Lewis Tseng, Son Nguyen, . Nitin. . Vaidya. The most widely used service that a bank offers. .. Money. on demand!. Benefits of a checking account. Convenience. Safety to make payments with less risk than using cash.. Proof of payment. A record of finances for managing your money.. Chapter 3: Probabilistic Query Answering (1). 2. Objectives. In this chapter, you will:. Learn the challenge of probabilistic query answering on uncertain data. Become familiar with the . framework for probabilistic . Chapter 3: Probabilistic Query Answering (1). 2. Objectives. In this chapter, you will:. Learn the challenge of probabilistic query answering on uncertain data. Become familiar with the . framework for probabilistic . Chapter 7: Probabilistic Query Answering (5). 2. Objectives. In this chapter, you will:. Explore the definitions of more probabilistic query types. Probabilistic skyline query. Probabilistic reverse skyline query. CS772A: Probabilistic Machine Learning. Piyush Rai. Course Logistics. Course Name: Probabilistic Machine Learning – . CS772A. 2 classes each week. Mon/. Thur. 18:00-19:30. Venue: KD-101. All material (readings etc) will be posted on course webpage (internal access). How Do People Gain Access to Money They Keep in the Bank?. Checking Account. Write a check. EFT = electronic funds transfer. Card swipe with PIN (personal identification number). Online banking. NOTE: . . OBJECTIVES. Explain. how checking accounts work. . Complete. a check register.. Slide. . 2. . . Key Terms. checking account. check. electronic funds transfer . (EFT). payee. drawer. check clearing. 3. Contents. Motivation. What. is . Bounded. Model . Checking. ?. Translation. from . Bounded. MC to SAT. Completeness. 01.11.2019. 4. Prerequisites. General Model Checking. Temporal Logic. 01.11.2019.