CS3341: Advanced Algorithms

Shanghai Jiao Tong University, Spring 2025

 

Course Information

InstructorKuan Yang
Lecture timesTuesday 10:00 - 11:40     (Week 1 - 16)
Friday     08:00 - 09:40     (Week 9 - 16)
LocationEast Upper Hall 105 (东上院 105)
Teaching assistant(s)Zhidan Li (李至丹) & Yao Xu (徐遥)
Office hoursTo be determined

 

News and Announcements

 

Textbook and References

 

Syllabus

  1. Randomized Algorithms and Probabilistic Techniques
  1. From Continuous to Discrete Optimization
  1. Markov Chain Monte Carlo Based Sampling

 

Lecture Schedule

WeekDateTopicsLecture notes
102/18Polynomial identity testingLecture 01
202/25Karger's min-cut, Linearity of expectationLecture 02
303/04Coupon collector, Karp-Upfal-Wigderson Bound 
403/11Balls-into-bins, Markov inequality, Monte Carlo vs. Las VegasLecture 03
503/18Chebyshev inequality, random graphs 
603/25Poisson approximation, Max load, Poisson processLecture 04
704/01Generalized coupon collector, Chernoff boundLecture 05
804/08Hoeffding inequality, Poisson tail bound 
904/15Martingale, Azuma-Hoeffding inequalityLecture 06
 04/18Optional stopping time, Wald's equation 
1004/22Lovász local lemmaLecture 07
 04/25Moser-Tardos algorithm 
1104/29Multiplicative Weights Update algorithm, convex functionsLecture 08
1205/06Separating hyperplane, convex functionsSeparating hyperplane
Convex functions
 05/08Convex optimization, gradient descentConvex optimization
Lecture 09
1305/13Lagrange multiplier method, KKT conditionLecture 10
 05/15Projected gradient descent, mirror descentLecture 11
Projected GD
1405/20MWU algorithm revisit, solving LP by MWULecture 12
 05/22Sampling problems, Markov chain basicsLecture 13
1505/27Total variation distance, coupling lemmaLecture 14
 05/29Metropolis algorithm, mixing time, coupling method 
1606/03Guest lecture by Chihao Zhang 
 06/05Final Quiz