PPT-CSCI 5822 Probabilistic Models of

Human and Machine Learning Mike Mozer Department of Computer Science and Institute of Cognitive Science University of Colorado at Boulder Hidden Markov Models Room Wandering Im going to wander around my house and tell you objects I see . . Natarajan. Introduction to Probabilistic Logical Models. Slides based on tutorials by . Kristian. . Kersting. , James . Cussens. , . Lise. . Getoor. . & Pedro . Domingos. Take-Away Message . 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. Tyler Lu and Craig . Boutilier. University of Toronto. Introduction. New communication platforms can transform the way people make group decisions.. How can . computational social choice . realize this shift?. (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. CSCI 201L. Jeffrey Miller, Ph.D.. http. ://www-scf.usc.edu/~csci201. USC CSCI 201L. Outline. USC CSCI 201L. 2. /8. Strings. Garbage Collection. Program. Strings. In Java there is a String class that abstracts a lot of the details away from the programmer. 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. Prithviraj Sen Amol Deshpande. outline. General Info. Introduction. Independent tuples . model. Tuple . correlations. Representing Dependencies. Query . evaluation. Experiments. Conclusions & Work to be done. 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. The UNIX System. Unit V. Permissions. Permissions. all access to directories and files is controlled. UNIX uses discretionary access control (DAC) model . each directory/file has owner. owner has discretion over access control details. Jeffrey Miller, Ph.D.. jeffrey.miller@usc.edu. Outline. Conditions. Program. USC CSCI 201L. Conditional Statements. Java has three conditional statements, similar to C . if-else. switch-case. Conditional ternary operator . Human and Machine Learning. Mike . Mozer. Department of Computer Science and. Institute of Cognitive Science. University of Colorado at Boulder. Flipping A Biased Coin. Suppose you have a coin with an unknown bias, . Human and Machine Learning. Mike . Mozer. Department of Computer Science and. Institute of Cognitive Science. University of Colorado at Boulder. Learning In Bayesian Networks:. Missing Data And Hidden Variables. Human and Machine Learning. Mike . Mozer. Department of Computer Science and. Institute of Cognitive Science. University of Colorado at Boulder. Flipping A Biased Coin. Suppose you have a coin with an unknown bias, . 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.