|Homework||Post Date||Due Date|
Office Hour: Tuesdays 3:00 - 5:00 PM at LSRC D226
Office Hour: Thursdays 5:00 - 7:00 PM at LSRC D309
Undergraduate Teaching Assistants
Office Hour: Wednesdays 12:00 - 2:00 PM at LSRC D309
Bodong (Wilson) Zhang
Office Hour: Mondays 10:00-11:00 AM at LSRC D301
Office Hour: Mondays 5:00 - 6:00 PM at LSRC D301
Weiyao (Will) Wang
Office Hour: Fridays 5:00 - 6:00 PM at LSRC D301
Office Hour: Mondays 7:00 - 8:00 PM at LSRC D301
Recitations: Fridays 3:05 - 4:20 PM, Physics 128
Text Book:Lecture notes will be uploaded on the course website after every lecture. In addition, the following books cover most of the syllabus:
There are two hard prerequisites (equivalent courses are also acceptable):
Evaluation:The grades will be determined by homework, midterm exam and final exam. Both exams are in-class closed-book exams.
Please submit through sakai.
Homework should be typed
and submit as a PDF file. Latex is highly preferred.
Please make sure to read the guideline on collaboration. Every incidence of cheating will be reported.
Questions about homework problems should be posted to Piazza (instead of emailing the TAs or the instructor).
|8/29||Intro: Algorithms, Asymptotic Notations||Notes
|Basic Algorithm Design Techniques|
|8/31||Divide and Conquer||Notes
2, KT 5, CLRS 4
6, KT 6, CLRS: 15
||DPV 5, KT 4, CLRS: 16|
||Graph representations and traversal||Notes||DPV 3, KT 3, CLRS 22|
|9/28||Shortest Paths algorithms||Notes||DPV: 4.6, 6.6 KT: 6.8
CLRS: 24.1, 25
||DPV: 5 KT: 4 CLRS: 16, 23|
|10/5||Bipartite Graphs, Maximum Matching||Notes||DPV 7 KT: 7 CLRS: 26|
|10/10||Fall break, No class|
|10/12||Review: How to find the right technique|
Exam (in class)
All materials in previous lectures.
||Notes||KT 4.6 CLRS 17, 20|
|10/26||Basic Probabilities, Quicksort revisited, fast selection||Notes||DPV: virtural chapger
CLRS: 5, 11
|10/31||Birthday Paradox, Coupon Collector, Balls in Bins||Notes|
|11/7||Linear Programming, Relaxations||Notes||CLRS 29|
|11/14||Linear Programming Algorithms||Notes|
|Machine Learning Algorithms|
|11/16||Basic Machine Learning, Principled Component Analysis||Slides Notes|
|11/21||Gradient Descent and Least Squares||Notes|
|11/28||P vs NP, reductions
||Notes||DPV: 8 KT: 8
|12/5||How to deal with NP-hard problems?
|12/7||Review/Information about Exam
|12/17||Final Exam 2 pm - 5pm|