Fundamental Data Structures
... data structure is index-based data structures, such as lists and hashtables. Each element is accessed by an index, which points to the position the element within the data structure. This is covered in Chapter 6 of the primary textbook[Conery(2011)]. In the three chapters of this handout, we will be ...
... data structure is index-based data structures, such as lists and hashtables. Each element is accessed by an index, which points to the position the element within the data structure. This is covered in Chapter 6 of the primary textbook[Conery(2011)]. In the three chapters of this handout, we will be ...
sorted
... A binary tree is either NULL or contains a node with the key/value pair, and a left and right child which are themselves trees. In a binary search tree (BST) the keys in the left child are smaller than the keys at the node and the values in the right child are greater than the value at the node. (Re ...
... A binary tree is either NULL or contains a node with the key/value pair, and a left and right child which are themselves trees. In a binary search tree (BST) the keys in the left child are smaller than the keys at the node and the values in the right child are greater than the value at the node. (Re ...
Unit III Linked Lists Variations
... One of the problems in dealing with pointer based ordered lists is writing code to take care of special cases. For example, if we wish to insert a node in an ordered linked list, we MUST take care of the special case of inserting this node in the beginning of the list. This is a special case because ...
... One of the problems in dealing with pointer based ordered lists is writing code to take care of special cases. For example, if we wish to insert a node in an ordered linked list, we MUST take care of the special case of inserting this node in the beginning of the list. This is a special case because ...
Data Structure Fusion - Stanford CS Theory
... data structures, namely a binary tree mapping each vertex to a list of its successors, together with the corresponding edge weights, and a binary tree mapping each vertex to a list of its predecessors, and the corresponding edge weights. One problem with our proposed ML representation is that the su ...
... data structures, namely a binary tree mapping each vertex to a list of its successors, together with the corresponding edge weights, and a binary tree mapping each vertex to a list of its predecessors, and the corresponding edge weights. One problem with our proposed ML representation is that the su ...
pptx
... • Maintain as unordered list – add() put new element at front – O(1) – poll() must search the list – O(n) – peek() must search the list – O(n) • Maintain as ordered list – add() must search the list – O(n) – poll() min element at front – O(1) – peek() O(1) Can we do better? ...
... • Maintain as unordered list – add() put new element at front – O(1) – poll() must search the list – O(n) – peek() must search the list – O(n) • Maintain as ordered list – add() must search the list – O(n) – poll() min element at front – O(1) – peek() O(1) Can we do better? ...
Advancing Front Method
... Consecutive points are joined by straight lines to form sides. In order to determine, the position and the number of nodes on each curve component, the following steps are followed: i- Subdivide each curve into smaller segments until their length is smaller that a certain prescribe value. The length ...
... Consecutive points are joined by straight lines to form sides. In order to determine, the position and the number of nodes on each curve component, the following steps are followed: i- Subdivide each curve into smaller segments until their length is smaller that a certain prescribe value. The length ...
Balanced BSTs
... of O(lg n) is guaranteed when implementing a dynamic set of n items. • Examples: ...
... of O(lg n) is guaranteed when implementing a dynamic set of n items. • Examples: ...
Selection and Search
... 1. Divide n elements into groups of 5 2. Find median of each group (How? How long?) 3. Use Select() recursively to find median x of the n/5 ...
... 1. Divide n elements into groups of 5 2. Find median of each group (How? How long?) 3. Use Select() recursively to find median x of the n/5 ...
R-Trees
... MINMAXDIST(p,R) is the minimum of the maximum distance to each pair of faces of R MaxDistanceToFace(p,R,k) = distance between p and Maxk= (M1,M2,..,Mk-1mk,MK+1,..,Mn) mi = closer of the two boundary points along i axis Mi = farther of the two boundary points along i axis ...
... MINMAXDIST(p,R) is the minimum of the maximum distance to each pair of faces of R MaxDistanceToFace(p,R,k) = distance between p and Maxk= (M1,M2,..,Mk-1mk,MK+1,..,Mn) mi = closer of the two boundary points along i axis Mi = farther of the two boundary points along i axis ...
AN EXAMINATION OF FAST SIMILARITY SEARCH TREES
... I would like to express my gratitude to my supervisor, Dr. Jeffrey Uhlmann, whose expertise, understanding, and patience, added considerably to my graduate experience. I have been amazingly fortunate to have an advisor who gave me the freedom to explore on my own, and at the same time the guidance t ...
... I would like to express my gratitude to my supervisor, Dr. Jeffrey Uhlmann, whose expertise, understanding, and patience, added considerably to my graduate experience. I have been amazingly fortunate to have an advisor who gave me the freedom to explore on my own, and at the same time the guidance t ...