Please come as early as possible on your chosen presentation day (10am Monday, 2:30 Tuesday, or 2:00 Wednesday) and if possible, stay until that day's presentations are done. The presentations will be much more rewarding for everyone if there's an audience!
Please register your group by filling out this Doodle poll no later than Friday, December 11. Please send Jeff email as soon as possible if your group cannot present at any of the available times.
Please fill out this Doodle poll to let me know when your group is available and willing to present. Each group should fill out the form once; enter the names of all group members, and only select times that the entire group can be present. Given the likely number of projects, we will need> at least three two-hour meetings to get through them all.
Written project reports are due Friday, December 18.
Friday's lecture (October 23) will end at 2:45, so that everyone can attend Andrew Yao's 3:00 lecture.
The first makeup lecture will be next Monday, October 26, 2:00-3:15. I'll announce the location (most likely in Siebel) by the end of the week.
I am traveling all next week, so class will be canceled; I will also miss two more lectures later in the semester. I've created a Doodle poll to help schedule a time for makeup lectures; please fill out the survey as soon as possible. Thanks!
All students who signed the waiting list have been offered registration overrides. If you are still interested but unable to add the class, please talk to Jeff as soon as possible.
As many of you have noticed, the class is full. Students who are still interested in taking the class are welcome to come to the lectures; I may be able to squeeze you in, especailly after a few people drop.
The class includes a significant number of undergraduates. Undergraduates are welcome, but please be aware that I will expect the same intellectual maturity, independence, and quality of work as graduate students in a top-5 computer science department.
This course will survey important developments in data structures that have not (yet) worked their way into the standard computer science curriculum. The precise topics will depend on the interests and background of the course participants; see the current schedule for details. Potential topics include include self-adjusting binary search trees, dynamic trees and graphs, persistent data structures, geometric data structures, kinetic data structures, I/O-efficient and cache-oblivious data structures, hash tables and Bloom filters, data structures that beat information-theoretic lower bounds, and applications of these data structures in computational geometry, combinatorial optimization, systems and networking, databases, and other areas of computer science.
Students in all areas of computer science and related disciplines are welcome, including algorithmically mature undergraduates. An undergrdauate algorithms class at the level of CS 473 is a prerequisite; specific background material will be introduced as needed.