Spring 1998 Course information page
[Section A]
[Section B]
[Section C]
[Section D]
[Course staff]
Have a great summer!
The Spring 1998 session of 15-299 is complete. The course materials
will be kept on this Web site until next year. Here are pointers
to resources that were used throughout the semester:
- Course Number: 15-299
- Credit: 12 units
- Lectures: Tues/Thurs 10:30-11:50, 2210 Doherty Hall
- Instructor: Bruce Maggs
- Office hours: Thurs. 2-3pm, 4123 Wean Hall (x8-7654)
- Email him at bmm+@cs
- Teaching assistants:
- Rob Miller
- Recitation section `A', 10:30-11:30 Mon. in 203 Student Center
- Office hours: Sun. 3-4pm, 5103 Wean Hall (x8-7571)
- Email him at rcm@cs
- Adam Kalai
- Recitation section `B', 11:30-12:20 Mon. in 203 Student Center
- Office hours: Mon. 3-4pm, 7113 Wean Hall (x8-7123)
- Email him at akalai@cs
- Hal Burch
- Recitation section `C', 12:30-1:20 Mon. in 203 Student Center
- Recitation section `D', 1:30-2:20 Mon. in 203 Student Center
- Office hours: Fri. 3-4pm, 7110 Wean Hall (x8-7670)
- Email him at hburch@cs
- Doug Beeferman
- Office hours: Thurs. 1-2pm, 5101 Wean Hall (x8-8139)
- Email him at dougb@cs
- Course secretary: Dorothy Zaborowski
- Office: 4116 Wean Hall (x8-3779)
- Email her at daz+@cs
Dramatis Personae
Course staff
- Bruce Maggs is
an Associate Professor in the Computer Science Department. His
research interests include parallel architectures and algorithms.
- Rob Miller is
a third-year graduate student in the Computer Science Department. His
research interests are in programming languages and user interfaces.
- Adam Kalai is
a second-year graduate student in the Computer Science Department.
His research interests include computer graphics, virtual
reality, and theoretical computer science.
- Hal Burch is
a first-year graduate student in the Computer Science Department.
His research interests include algorithms and scientific computing.
- Doug Beeferman is
a third-year graduate student in the Computer Science Department.
His research interests include natural language modeling and
artificial intelligence.
The Ideas
- Counting: Learn how to count without counting.
- Induction: Recognize it in all its guises.
- Exemplification: Find a sense in which you can try out a problem
or solution on small examples.
- Abstraction: Abstract away the inessential features of a problem.
- Modularity: Decompose a complex problem into simpler subproblems.
- Representation: Understand the relationships between different
possible representations of the same information or idea.
- Refinement: The best solutions come from a process of repeatedly
refining and inventing alternative solutions.
- Toolbox: Build up your vocabulary of abstract structures.
- Optimization: Understand which improvements are worth it.
- Probabilistic methods: Flipping a coin can be surprisingly helpful!
How to get electronic course information
- Use the Web browser of your choice and visit this page often!
Click here
for Netscape's official handbook on using its Navigator 3.0 browser.
Regardless of which browser you choose, you can probably access a similar
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- You should also read the class newsgroups regularly.
If the following addresses are not accessible, please use messages or batmail
to read the newsgroups. You can post via email by sending to
bb+academic.cs.15-299.discuss@andrew.cmu.edu.
Send email to the maintainer of this page.