Experimental Analysis of Algorithms

Lectures

• Lecture 1
• Lecture 2
  Bibliography: Applied Mathematical Programming. Ch9. Integer Programming
  Artificial Intelligence: A Modern Approach Ch5. Constraint Satisfaction Problems
• Lecture 3
  Bibliography: Fibonacci Heaps, Introduction to Randomized Algorithms
• Lecture 4
  Bibliography: AIMA-ch3.4,3.5
• Lecture 5
  Bibliography: Introduction to Algorithms. Ch17. Amortized Analysis
  Smoothed Analysis of Local Search
• Lecture 6
Bibliography: Graph representation learning
• Lecture 7
  Bibliography: External Memory Algorithms and Data Structures
• Lecture 8
  Bibliography: M. Baron. Probability and Statistics for Computer Scientists. Ch8 Introduction to Statistics
• Lecture 9
  Bibliography: M. Baron. Probability and Statistics for Computer Scientists. Ch9 Statistical Inference I, Ch10 Statistical Inference II
• Lecture 10a
  
• Lecture 10b
  
• Lecture 11
  

Labs

Bibliography

• Algorithm Engineering: Bridging the Gap Between Algorithm Theory and Practice, M. Muller-Hannemann, S. Schira (Eds.), Springer-Verlag, 2010
• A Guide to Experimental Algorithmics, C. McGeoch, Cambridge University Press, 2012
• Experimental Methods for the Analysis of Optimization Algorithms, T. Bartz-Beielstein, M. Chiarandini, L. Paquete, M. Preuss (Eds.), Springer-Verlag, 2010
• Mathematical Statistics and Data Analysis, J.A. Rice, Duxbury Press, 2006