PPT-Probabilistic Data Management

Chapter 5 Probabilistic Query Answering 3 2 Objectives In this chapter you will Learn the definition and query processing techniques of a probabilistic query type Probabilistic Reverse Nearest Neighbor Query. Component-Based Shape Synthesis. Evangelos. . Kalogerakis. , . Siddhartha . Chaudhuri. , . Daphne . Koller. , . Vladlen. . Koltun. Stanford . University. Goal: generative model of shape. Goal: generative model of shape. David Kauchak. CS451 – Fall 2013. Admin. Assignment 6. Assignment . 7. CS Lunch on Thursday. Midterm. Midterm. mean: 37. median: 38. Probabilistic Modeling. training data. probabilistic model. train. Bhargav Kanagal & Amol Deshpande. University of Maryland. Introduction. Correlated Probabilistic data generated in many scenarios. Data Integration [AFM06]: Conflicting information best captured using “mutual exclusivity”. (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. Shou-pon. 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. Ashish Srivastava. Harshil Pathak. Introduction to Probabilistic Automaton. Deterministic Probabilistic Finite Automata. Probabilistic Finite Automaton. Probably Approximately Correct (PAC) learnability. 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. Pérez. Nicolás. . Suárez. CRIDA A.I.E.. COmbining. Probable . TRAjectories. — COPTRA. Brussels 5. th. of October . 2016. COmbining. Probable . TRAjectories. — COPTRA. 2. Introduction. COPTRA . 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 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. 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. Hybrid . Recommender Systems. Pigi Kouki, . Shobeir. . Fakhraei. , . James . Foulds. , . Magdalini. . Eirinaki. , . Lise. . Getoor. University . of California, Santa Cruz . University of Maryland, College . Assessing risk, . considering chances and uncertainties.. What is Probability?. “A strong likelihood or chance of something” (dictionary.com). “The likelihood of something occurring or the chance of something happening” (yourdictionary.com). 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).