STAT 538 Handout 0

S T A T 5 3 5 S t a t i s t i c a l C o m p u t i n g

Handout 0 - About the course

Lecture place and time: Tuesdays & Thursdays 11:30 - 12:50 in LOW 106

Course web site: http://www.stat.washington.edu/courses/stat538/winter08 Use it!

Instructor: Marina Meila

mmp@stat.washington.edu

Office hours: Monday 2-3pm in PDL B-321 (if there are no major conflicts)
Class mailing list: To be set up

Textbooks: Boyd & Van der Berghe -- required, Bertsekas and Numerical Recipes recommended. See the Resources page for links to on-line versions of these books.
Occasionally I will hand out other reading materials in class or post them on the web.
Format: The course will consist of two weekly lectures, a series of homework assignments and a project. Active class participation by questions, answers and comments is important and therefore it will be part of your grade.
Assignments: Typically assignments will be handed out on Tuesdays and will be due the next Tuesday before class. The assignments will consist of (1) short programming assignments (typically, to implement a version or a special case of an algorithm presented in class) to be done in the programming language of your choice and (2) algorithm problems or other questions related to the graphical models we will be studying. The programming assignments will be split into two parts: output and results, which should be handed in on paper, and that will be graded, and the code part, which is submitted electronically and is typically not graded. Late homeworks will only be accepted in exceptional circumstances.
Teamwork: Each class participant submits her/his homework individually. Unless explicitly allowed to do so, you are required to write your own code.
Grading: (Approximately) 20% class participation 40% assignments and 40% project. There will be no final exam.
Prerequisites: See the

Instructor:	Marina Meila
	mmp@stat.washington.edu
Office hours:	Monday 2-3pm in PDL B-321 (if there are no major conflicts)
Class mailing list:	To be set up
Textbooks:	Boyd & Van der Berghe -- required, Bertsekas and Numerical Recipes recommended. See the Resources page for links to on-line versions of these books. Occasionally I will hand out other reading materials in class or post them on the web.
Format:	The course will consist of two weekly lectures, a series of homework assignments and a project. Active class participation by questions, answers and comments is important and therefore it will be part of your grade.
Assignments:	Typically assignments will be handed out on Tuesdays and will be due the next Tuesday before class. The assignments will consist of (1) short programming assignments (typically, to implement a version or a special case of an algorithm presented in class) to be done in the programming language of your choice and (2) algorithm problems or other questions related to the graphical models we will be studying. The programming assignments will be split into two parts: output and results, which should be handed in on paper, and that will be graded, and the code part, which is submitted electronically and is typically not graded. Late homeworks will only be accepted in exceptional circumstances.
Teamwork:	Each class participant submits her/his homework individually. Unless explicitly allowed to do so, you are required to write your own code.
Grading:	(Approximately) 20% class participation 40% assignments and 40% project. There will be no final exam.
Prerequisites:	See the