Algorithms - By Shai Simonson (Size: 3.5 GB)
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| | | Rubik's Cube.htm | 13.04 KB |
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| | | Second Attempt O(n).htm | 9.36 KB |
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| | | Floyd-Warshall (ADU Feb 15).htm | 8.43 KB |
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| | | The Ford-Fulkerson Algorithm in C.htm | 5.12 KB |
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| | | Knight Tour.htm | 2.07 KB |
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| | | Breadth-First Search.htm | 3.78 KB |
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| | | Developing a Dynamic Programming algorithm.htm | 2.76 KB |
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| | | Preventing an Array-Index-Out-Of-Bound Error.htm | 4.83 KB |
| | | general_info.pdf | 2.75 KB |
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| | | lecture_notes1.pdf | 84.5 KB |
| | | lecture_notes2.pdf | 30.32 KB |
| | | Problem Set 1 Solutions.pdf | 1.21 MB |
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| | | Problem Set 6_ NP-Complete Reductions.pdf | 1.08 MB |
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| | | Problem_Set_02_Solutions.pdf | 84.1 KB |
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| | | 9.Graph Algoritms 4 - Intro to Geometric Algorithms.ram | 201.17 MB |
| | | 2.Sorting.ram | 200.55 MB |
| | | 8.Graph Algoritms 3 - Shortest Path.ram | 195.23 MB |
| | | 5.Red-Black Trees.ram | 192.11 MB |
| | | 6.Graph Algorithms 1 - Topological Sorting,Prim's Algorithm.ram | 186.53 MB |
| | | 1.Algorithms-Overview.ram | 186.02 MB |
| | | 18.Np Completeness 4.ram | 185.31 MB |
| | | 11.Dynamic Programming 1 of 2.ram | 184.87 MB |
| | | 13.Parsing.ram | 181.32 MB |
| | | 3.Sorting 2.ram | 180.95 MB |
| | | Algorithms - Lectures and Courseware.png | 303.18 KB |
| | | Contents - Algorithms.png | 183.07 KB |
| | | syllabus.pdf | 7.31 KB |
Description
Algorithms
Instructor: Shai Simonson
The design of algorithms is studied, according to methodology and application. Methodologies include: divide and conquer, dynamic programming, and greedy strategies. Applications involve: sorting, ordering and searching, graph algorithms, geometric algorithms, mathematical (number theory, algebra and linear algebra) algorithms, and string matching algorithms. Analysis of algorithms is studied - worst case, average case, and amortized - with an emphasis on the close connection between the time complexity of an algorithm and the underlying data structures. NP-Completeness theory is examined along with methods of coping with intractability, such as approximation and probabilistic algorithms.
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