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Free Download - Design and Analysis of Computer Algorithms – Lecture Notes : By David M. Mount.


Title      :  Design and Analysis of Computer 
            Algorithms – Lecture Notes
Author  :  David M. Mount,
               Department of Computer Science,
               University of Maryland.

BOOK Length : 135 pages
BOOK File Format : PDF
BOOK Language : English


BOOK Description :

Table of Contents
  • Lecture - 1 : Course Introduction
  • Lecture - 2 : Mathematical Background
  • Lecture - 3 : Review of Sorting and selection
  • Lecture - 4 : Dynamic Programming : Longest Common Subsequence
  • Lecture - 5 : Dynamic Programming : Chain Matrix Multiplication
  • Lecture - 6 : Dynamic Programming : Minimum Weight Triangulation
  • Lecture - 7 : Greedy Algorithms : Activity Selection and Fractional Knapack
  • Lecture - 8 : Greedy Algorithms : Huffman Coding
  • Lecture - 9 : Graphs : Background and Breadth First Search
  • Lecture - 10 : Depth - First Search
  • Lecture - 11 : Topological Sort and Strong Components
  • Lecture - 12 : Minimum Spanning Trees and Kruskal’s Algorithm
  • Lecture - 13 : Prim’s and Baruvka’s Algorithms for MSTs 
  • Lecture - 14 : Dijkstra’s Algorithm for Shortest Paths
  • Lecture - 15 : All-Pairs Shortest Paths
  • Lecture - 16 : NP-Completeness : Languages and NP
  • Lecture - 17 : NP-Completeness : Reductions
  • Lecture - 18 : Cook’s Theorem, 3SAT, and Independent Set
  • Lecture - 19 : Clique, Vertex Cover, and Dominating Set
  • Lecture - 20 : Subset Sum
  • Lecture - 21 : Approximation Algorithms : VC and TSP 
  • Lecture - 22 : The k-Center Approximation
  • Lecture - 23 : Approximations : Set Cover and Bin Packing
  • Lecture - 24 : Final Review
  • Supplemental Lecture - 1 : Asymptotic s
  • Supplemental Lecture - 2 : Max Dominance
  • Supplemental Lecture - 3 : Recurrences and Generating Functions
  • Supplemental Lecture - 4 : Medians and Selection
  • Supplemental Lecture - 5 : Analysis of Bucket Sort
  • Supplemental Lecture - 6 : Long Integer Multiplication
  • Supplemental Lecture - 7 : Dynamic Programming : 0–1 Knapsack Problem
  • Supplemental Lecture - 8 : Dynamic Programming : Memorization
  • Supplemental Lecture - 9 : Articulation Points and Bi-connectivity
  • Supplemental Lecture - 10 : Bellman-Ford Shortest Paths
  • Supplemental Lecture - 11 : Network Flows and Matching
  • Supplemental Lecture - 12 : Hamiltonian Path
  • Supplemental Lecture - 13 : Subset Sum Approximation

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