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Disjoint Sets: Data Structures and Algorithms

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Manage episode 466139360 series 3628532
Content provided by AmCan Tech. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AmCan Tech or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
We discuss disjoint sets, also known as union-find data structures. Disjoint sets maintain collections of elements partitioned into non-overlapping sets, each with a representative element. Key operations include Make-Set (creating a new set), Find-Set (locating a set's representative), and Union (merging two sets). Different representations are explored, such as arrays, linked lists, and inverted trees, along with their associated time complexities. Heuristics like weighted union and union by rank are introduced to improve efficiency, and path compression is discussed as a way to optimize the Find-Set operation. The notes culminate in discussing the inverse Ackermann function in the context of the time complexity of the union by rank and path compression methods.
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17 episodes

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iconShare
 
Manage episode 466139360 series 3628532
Content provided by AmCan Tech. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by AmCan Tech or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
We discuss disjoint sets, also known as union-find data structures. Disjoint sets maintain collections of elements partitioned into non-overlapping sets, each with a representative element. Key operations include Make-Set (creating a new set), Find-Set (locating a set's representative), and Union (merging two sets). Different representations are explored, such as arrays, linked lists, and inverted trees, along with their associated time complexities. Heuristics like weighted union and union by rank are introduced to improve efficiency, and path compression is discussed as a way to optimize the Find-Set operation. The notes culminate in discussing the inverse Ackermann function in the context of the time complexity of the union by rank and path compression methods.
  continue reading

17 episodes

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