Document
... else return -1 else // divide P into two smaller subproblems mid = (low + high) / 2 if (x == a[mid]) then return mid else if (x < a[mid]) then return BinSearch(a, low, mid-1, x) else return BinSearch(a, mid+1, high, x) ...
... else return -1 else // divide P into two smaller subproblems mid = (low + high) / 2 if (x == a[mid]) then return mid else if (x < a[mid]) then return BinSearch(a, low, mid-1, x) else return BinSearch(a, mid+1, high, x) ...
The Scala Experience Safe Programming Can be Fun!
... • Size of the inspected array: n n/2 n/4 ….. 1 • Each step is very fast (a small constant number of operations) • There are log2(n) such steps • So it takes ~ log2(n) steps per search • Much faster then ~ n ...
... • Size of the inspected array: n n/2 n/4 ….. 1 • Each step is very fast (a small constant number of operations) • There are log2(n) such steps • So it takes ~ log2(n) steps per search • Much faster then ~ n ...
pptx - Neural Network and Machine Learning Laboratory
... Monte Carlo algorithms have a consistent time complexity, but there is a probability of returning an incorrect/poor answer – Can flexibly increase time to improve chance of a correct answer ...
... Monte Carlo algorithms have a consistent time complexity, but there is a probability of returning an incorrect/poor answer – Can flexibly increase time to improve chance of a correct answer ...
Absolute o(logm) error in approximating random set covering: an
... number of subsets is polynomially bounded by the number of ground elements. This condition holds in most real world SC instances, and ensures that the instance is nontrivial with high probability: e.g., an exponential in m number of random subsets created through independent Bernoulli trials, subsum ...
... number of subsets is polynomially bounded by the number of ground elements. This condition holds in most real world SC instances, and ensures that the instance is nontrivial with high probability: e.g., an exponential in m number of random subsets created through independent Bernoulli trials, subsum ...
UNIT-I - WordPress.com
... Distinguish between Algorithm and Pseudocode. • An algorithm is a well-defined sequence of steps that provides a solution for a given problem, while a pseudocode is one of the methods that can be used to represent an algorithm. • Algorithms can be written in natural language, pseudocode is written ...
... Distinguish between Algorithm and Pseudocode. • An algorithm is a well-defined sequence of steps that provides a solution for a given problem, while a pseudocode is one of the methods that can be used to represent an algorithm. • Algorithms can be written in natural language, pseudocode is written ...
Arrays
... sort(array), sort(array, fromIndex, toIndex) All elements in the array must implement the Comparable interface sort(array, comparator) sort(array, fromIndex, toIndex, comparator) All elements in the array must be mutually comparable by the specified comparator ...
... sort(array), sort(array, fromIndex, toIndex) All elements in the array must implement the Comparable interface sort(array, comparator) sort(array, fromIndex, toIndex, comparator) All elements in the array must be mutually comparable by the specified comparator ...
Mouse in a Maze - Bowdoin College
... • An algorithm is not unique!!! • There are many ways to solve a problem • Moreover, given a certain way to solve a problem, there are many ways to express that into pseudocode!! • Etiquette: – Give variables meaningful names – Write explanations/comments of what your code does ...
... • An algorithm is not unique!!! • There are many ways to solve a problem • Moreover, given a certain way to solve a problem, there are many ways to express that into pseudocode!! • Etiquette: – Give variables meaningful names – Write explanations/comments of what your code does ...
Factorization of a Large number
... To find the optimal amount of computation a thread should compute when using CUDA devices Idea (Steps) ...
... To find the optimal amount of computation a thread should compute when using CUDA devices Idea (Steps) ...
Program revision 2
... values. All of the values in an array must be of the same type. The type of the array is the type of the values it holds, followed by the characters []. An index is used to refer to individual values in the array. If we have N values, we think of them as being numbered from 0 to N-1. Each cell of th ...
... values. All of the values in an array must be of the same type. The type of the array is the type of the values it holds, followed by the characters []. An index is used to refer to individual values in the array. If we have N values, we think of them as being numbered from 0 to N-1. Each cell of th ...
Algorithms Design and Analysis Ch1: Analysis Basics
... Algorithms are all around us in everyday life. In the recipe of a cook book. In assembling a toy. In setting the table. In preparing a cup of tea. In calling your friend on the phone. …. There are countless examples! ...
... Algorithms are all around us in everyday life. In the recipe of a cook book. In assembling a toy. In setting the table. In preparing a cup of tea. In calling your friend on the phone. …. There are countless examples! ...
The counting problem
... How to do it: Step 1. (initialization) pos=-1; Step 2. (repetition) repeat for each index in range 0,1,2,…,n-1 test if a[i]==X then record the position pos=i; ...
... How to do it: Step 1. (initialization) pos=-1; Step 2. (repetition) repeat for each index in range 0,1,2,…,n-1 test if a[i]==X then record the position pos=i; ...
Suppose we are given the problem Minimize z = -19x 1 - 13x 2
... do not calculate c 1 , because x1 is basic which implies that c 1 = 0.) ...
... do not calculate c 1 , because x1 is basic which implies that c 1 = 0.) ...
ppt - Multimedia at UCC
... How to do it: Step 1. (initialization) pos=-1; Step 2. (repetition) repeat for each index in range 0,1,2,…,n-1 test if a[i]==X then record the position pos=i; ...
... How to do it: Step 1. (initialization) pos=-1; Step 2. (repetition) repeat for each index in range 0,1,2,…,n-1 test if a[i]==X then record the position pos=i; ...
File
... • For example, stack and queue are perfect examples of an abstract data type. We can implement both these ADTs using an array or a linked list. This demonstrates the "abstract" nature of stacks and ...
... • For example, stack and queue are perfect examples of an abstract data type. We can implement both these ADTs using an array or a linked list. This demonstrates the "abstract" nature of stacks and ...
Probabilistic Skyline Operator over sliding Windows
... anti-correlated dataset. For 5d anti-correlated data, our algorithm can still support up to 728 elements per second, which is a medium speed for data streams. ...
... anti-correlated dataset. For 5d anti-correlated data, our algorithm can still support up to 728 elements per second, which is a medium speed for data streams. ...
Dynamic Programming
... problem just once and then Saves its answer in a table (array), there by Avoiding the work of recomputing the answer every time the sub problem is encountered. Dynamic programming is typically applied to optimization problems. What is an optimization problem? There can be may possible solutions ...
... problem just once and then Saves its answer in a table (array), there by Avoiding the work of recomputing the answer every time the sub problem is encountered. Dynamic programming is typically applied to optimization problems. What is an optimization problem? There can be may possible solutions ...
Document
... • Space complexity: the computer memory required to solve a problem of a specified size. The time complexity is expressed in terms of the number of operations used by the algorithm. ...
... • Space complexity: the computer memory required to solve a problem of a specified size. The time complexity is expressed in terms of the number of operations used by the algorithm. ...
Document
... • Space complexity: the computer memory required to solve a problem of a specified size. The time complexity is expressed in terms of the number of operations used by the algorithm. ...
... • Space complexity: the computer memory required to solve a problem of a specified size. The time complexity is expressed in terms of the number of operations used by the algorithm. ...
Quicksort
Quicksort (sometimes called partition-exchange sort) is an efficient sorting algorithm, serving as a systematic method for placing the elements of an array in order. Developed by Tony Hoare in 1959, with his work published in 1961, it is still a commonly used algorithm for sorting. When implemented well, it can be about two or three times faster than its main competitors, merge sort and heapsort.Quicksort is a comparison sort, meaning that it can sort items of any type for which a ""less-than"" relation (formally, a total order) is defined. In efficient implementations it is not a stable sort, meaning that the relative order of equal sort items is not preserved. Quicksort can operate in-place on an array, requiring small additional amounts of memory to perform the sorting.Mathematical analysis of quicksort shows that, on average, the algorithm takes O(n log n) comparisons to sort n items. In the worst case, it makes O(n2) comparisons, though this behavior is rare.