on queue - Text of NPTEL IIT Video Lectures
... What will happen when it becomes empty? Suppose if I kept removing the elements starting from the f th location, I did not add any other element and then I removed all the elements before r th location. Where f would be located? f would be increment to r, so f becomes r. When f is r, queue is empty. ...
... What will happen when it becomes empty? Suppose if I kept removing the elements starting from the f th location, I did not add any other element and then I removed all the elements before r th location. Where f would be located? f would be increment to r, so f becomes r. When f is r, queue is empty. ...
LSH Forest: Self-Tuning Indexes for Similarity Search
... the number of points n, the index returns an -approximate nearest neighbor for q. Furthermore, the number of points examined by the query is strictly sub-linear in n and the storage overhead for the index is sub-quadratic in n. Observe the important caveat however: we need to know the distance r fr ...
... the number of points n, the index returns an -approximate nearest neighbor for q. Furthermore, the number of points examined by the query is strictly sub-linear in n and the storage overhead for the index is sub-quadratic in n. Observe the important caveat however: we need to know the distance r fr ...
SMALTA: Practical and Near
... interest) in the FIB. Indeed we found that the improvement in terms of FIB memory is about 12% less than the improvement in terms of number of entries. SMALTA is a provably correct incremental FIB aggregation scheme also based on ORTC. In addition to the correctness proof, we automatically computed ...
... interest) in the FIB. Indeed we found that the improvement in terms of FIB memory is about 12% less than the improvement in terms of number of entries. SMALTA is a provably correct incremental FIB aggregation scheme also based on ORTC. In addition to the correctness proof, we automatically computed ...
Glass Box Software Model Checking
... the figure. Thus, if these nodes remain unchanged, the insert operation will behave similarly (e.g., on trees t2 and t3). At this point we would like to conclude that it is redundant to check the operation on t1, t2, and t3. Then we could only check t1 and achieve a high degree of state space reduct ...
... the figure. Thus, if these nodes remain unchanged, the insert operation will behave similarly (e.g., on trees t2 and t3). At this point we would like to conclude that it is redundant to check the operation on t1, t2, and t3. Then we could only check t1 and achieve a high degree of state space reduct ...
New Data Structures for Orthogonal Range Searching
... be at most ⌈2m/f (m)⌉ columns and ⌈2m/f (m)⌉ rows. We define the top set of points Ŝ ⊆ [⌈2m/f (m)⌉]2 by (i, j) ∈ Ŝ if and only if Q(i, j) 6= ∅. A range query for the query rectangle [a, b] × [c, d] ⊆ [u] × [u] can be expressed in terms of range queries for the above sets. We split between two case ...
... be at most ⌈2m/f (m)⌉ columns and ⌈2m/f (m)⌉ rows. We define the top set of points Ŝ ⊆ [⌈2m/f (m)⌉]2 by (i, j) ∈ Ŝ if and only if Q(i, j) 6= ∅. A range query for the query rectangle [a, b] × [c, d] ⊆ [u] × [u] can be expressed in terms of range queries for the above sets. We split between two case ...
Recursive Data Structure Profiling
... few RDS instances with a large number of nodes. As we will see later, this problem can be avoided if we are able to categorize the edges of the USG into the RDS instances to which they belong, on the fly. We need to keep track of those connected components of the USG that correspond to the RDS insta ...
... few RDS instances with a large number of nodes. As we will see later, this problem can be avoided if we are able to categorize the edges of the USG into the RDS instances to which they belong, on the fly. We need to keep track of those connected components of the USG that correspond to the RDS insta ...
2. Non-Linear Data Structure: - In non linear data
... Note: Implementation of data structures using pointers is efficient than implementing using arrays. It gives more flexibility for the operation. Operations on Linear data structures: The operations one normally performs on any linear structure, whether it be an array or a linked list, include the fo ...
... Note: Implementation of data structures using pointers is efficient than implementing using arrays. It gives more flexibility for the operation. Operations on Linear data structures: The operations one normally performs on any linear structure, whether it be an array or a linked list, include the fo ...
Fundamental Data Structures
... Relation between amortized and actual time . . . . . . . . . . . . . . . . . . . . . . . . . ...
... Relation between amortized and actual time . . . . . . . . . . . . . . . . . . . . . . . . . ...
Functional Data Structures
... point of view of designing and implementing ecient data structures, functional programming's stricture against destructive updates (assignments) is a staggering handicap, tantamount to con scating a master chef's knives. Like knives, destructive updates can be dangerous when misused, but tremendous ...
... point of view of designing and implementing ecient data structures, functional programming's stricture against destructive updates (assignments) is a staggering handicap, tantamount to con scating a master chef's knives. Like knives, destructive updates can be dangerous when misused, but tremendous ...
A Practical Introduction to Data Structures and Algorithm
... data structures will also benefit from having first completed a good course in Discrete Mathematics. Nonetheless, Chapter 2 attempts to give a reasonably complete survey of the prerequisite mathematical topics at the level necessary to understand their use in this book. Readers may wish to refer bac ...
... data structures will also benefit from having first completed a good course in Discrete Mathematics. Nonetheless, Chapter 2 attempts to give a reasonably complete survey of the prerequisite mathematical topics at the level necessary to understand their use in this book. Readers may wish to refer bac ...
Computer Science E-119 Data Structures
... • Given a large collection of data, how can we arrange it so that we can efficiently: • add a new item • search for an existing item • Some data structures provide better performance than others for this application. • More generally, we’ll learn how to characterize the efficiency of different data ...
... • Given a large collection of data, how can we arrange it so that we can efficiently: • add a new item • search for an existing item • Some data structures provide better performance than others for this application. • More generally, we’ll learn how to characterize the efficiency of different data ...
Part III Data Structures
... the left sub-tree of a node v have a smaller key-value than key[v] and elements in the right sub-tree have a larger-key value. We assume that all key-values are different. ...
... the left sub-tree of a node v have a smaller key-value than key[v] and elements in the right sub-tree have a larger-key value. We assume that all key-values are different. ...
Implicit Data Structures, Sorting, and Text Indexing
... in Partial Fulfillment of the Requirements for the PhD Degree ...
... in Partial Fulfillment of the Requirements for the PhD Degree ...
Scalable Mining for Classification Rules in
... use random sampling in places where it is appropriate. In [MAR96, SAM96, IBM96], data access for classi cation follows \a record at a time" access paradigm. Scalability is addressed individually for each operating system, hardware platform, and architecture. In this paper, we introduce the MIND (MIN ...
... use random sampling in places where it is appropriate. In [MAR96, SAM96, IBM96], data access for classi cation follows \a record at a time" access paradigm. Scalability is addressed individually for each operating system, hardware platform, and architecture. In this paper, we introduce the MIND (MIN ...
Prim`s Algorithm
... array provides a convenient structure for representing data; it is classified as one of the data structures in C. An array is a sequenced collection of related data items that share a common name. The array occupies the contiguous memory block to store large volume of data. Array based on static mem ...
... array provides a convenient structure for representing data; it is classified as one of the data structures in C. An array is a sequenced collection of related data items that share a common name. The array occupies the contiguous memory block to store large volume of data. Array based on static mem ...
Oblivious Data Structures - Cryptology ePrint Archive
... scenarios in mind. For the outsourced cloud storage and secure processor settings, bandwidth blowup is the key metric; whereas for a secure computation setting, we consider the number of AES encryptions necessary to perform each data structure operation. Our simulation shows an order of magnitude sp ...
... scenarios in mind. For the outsourced cloud storage and secure processor settings, bandwidth blowup is the key metric; whereas for a secure computation setting, we consider the number of AES encryptions necessary to perform each data structure operation. Our simulation shows an order of magnitude sp ...
Algorithms and Data Structures
... Ý insertItem(k,e): inserts an item with key k and element e Ý removeMin(): removes the item with the smallest key and returns its element Ý minKey(): returns the smallest key of an item (no removal) Ý minElement(): returns the element of an item with smallest key (no removal) ...
... Ý insertItem(k,e): inserts an item with key k and element e Ý removeMin(): removes the item with the smallest key and returns its element Ý minKey(): returns the smallest key of an item (no removal) Ý minElement(): returns the element of an item with smallest key (no removal) ...
Optimal Bounds for the Predecessor Problem and
... packed b/k to a word, for a total of O(Nk/b) words. For example, for membership queries, k=1. In this special case, updates to the table can also be performed in constant time. If the universe size N is significantly less than 2 b, where b is the number of bits in a word, then packed B-trees [6, 12, ...
... packed b/k to a word, for a total of O(Nk/b) words. For example, for membership queries, k=1. In this special case, updates to the table can also be performed in constant time. If the universe size N is significantly less than 2 b, where b is the number of bits in a word, then packed B-trees [6, 12, ...