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Dynamic Optimality
In computer science, an optimal binary search tree (Optimal BST), sometimes called a weight-balanced binary tree, is a binary search tree which provides the smallest possible search time (or expected search time) for a given sequence of accesses (or access probabilities). Optimal BSTs are generally divided into two types: static and dynamic. In the static optimality problem, the tree cannot be modified after it has been constructed. In this case, there exists some particular layout of the nodes of the tree which provides the smallest expected search time for the given access probabilities. Various algorithms exist to construct or approximate the statically optimal tree given the information on the access probabilities of the elements. In the dynamic optimality problem, the tree can be modified at any time, typically by permitting tree rotations. The tree is considered to have a cursor starting at the root which it can move or use to perform modifications. In this case, there exis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computer Science
Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines (such as algorithms, theory of computation, information theory, and automation) to Applied science, practical disciplines (including the design and implementation of Computer architecture, hardware and Computer programming, software). Computer science is generally considered an area of research, academic research and distinct from computer programming. Algorithms and data structures are central to computer science. The theory of computation concerns abstract models of computation and general classes of computational problem, problems that can be solved using them. The fields of cryptography and computer security involve studying the means for secure communication and for preventing Vulnerability (computing), security vulnerabilities. Computer graphics (computer science), Computer graphics and computational geometry address the generation of images. Progr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Garsia–Wachs Algorithm
The Garsia–Wachs algorithm is an efficient method for computers to construct optimal binary search trees and alphabetic Huffman codes, in linearithmic time. It is named after Adriano Garsia and Michelle L. Wachs. Problem description The input to the problem, for an integer n, consists of a sequence of n+1 non-negative weights w_0,w_1,\dots, w_n. The output is a rooted binary tree with n internal nodes, each having exactly two children. Such a tree has exactly n+1 leaf nodes, which can be identified (in the order given by the binary tree) with the n+1 input weights. The goal of the problem is to find a tree, among all of the possible trees with n internal nodes, that minimizes the weighted sum of the ''external path lengths''. These path lengths are the numbers of steps from the root to each leaf. They are multiplied by the weight of the leaf and then summed to give the quality of the overall tree. This problem can be interpreted as a problem of constructing a binary search tre ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Interleave Lower Bound
In the theory of optimal binary search trees, the interleave lower bound is a lower bound on the number of operations required by a Binary Search Tree (BST) to execute a given sequence of accesses. Several variants of this lower bound have been proven. This article is based on a variation of the first Wilber's bound. This lower bound is used in the design and analysis of Tango tree. Furthermore, this lower bound can be rephrased and proven geometrically, Geometry of binary search trees. Definition The bound is based on a fixed ''perfect BST'' P , called the lower bound tree, over the keys \. For example, for n = 7 , P can be represented by the following parenthesis structure: :: .html"_;"title="[1">[12_[3_4_([5.html" ;"title="">[12_[3.html" ;"title=".html" ;"title="[1">[12 [3">.html" ;"title="[1">[12 [3 4 ([5">">[12_[3.html" ;"title=".html" ;"title="[1">[12 [3">.html" ;"title="[1">[12 [3 4 ([56 [7])] For each node y in P , define: * Left(y) to be the set of nodes i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Arborally Satisfied
In computer science, one approach to the dynamic optimality problem on online algorithms for binary search trees involves reformulating the problem geometrically, in terms of augmenting a set of points in the plane with as few additional points as possible in order to avoid rectangles with only two points on their boundary. Access sequences and competitive ratio As typically formulated, the online binary search tree problem involves search trees defined over a fixed key set \. An ''access sequence'' is a sequence x_1, x_2, ... where each access x_i belongs to the key set. Any particular algorithm for maintaining binary search trees (such as the splay tree algorithm or Iacono's working set structure) has a ''cost'' for each access sequence that models the amount of time it would take to use the structure to search for each of the keys in the access sequence in turn. The cost of a search is modeled by assuming that the search tree algorithm has a single pointer into a binary search ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Geometry Of Binary Search Trees
In computer science, one approach to the dynamic optimality problem on online algorithms for binary search trees involves reformulating the problem geometrically, in terms of augmenting a set of points in the plane with as few additional points as possible in order to avoid rectangles with only two points on their boundary. Access sequences and competitive ratio As typically formulated, the online binary search tree problem involves search trees defined over a fixed key set \. An ''access sequence'' is a sequence x_1, x_2, ... where each access x_i belongs to the key set. Any particular algorithm for maintaining binary search trees (such as the splay tree algorithm or Iacono's working set structure) has a ''cost'' for each access sequence that models the amount of time it would take to use the structure to search for each of the keys in the access sequence in turn. The cost of a search is modeled by assuming that the search tree algorithm has a single pointer into a binary search ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
John Iacono
John Iacono is an American computer scientist specializing in data structures, algorithms and computational geometry. He is one of the inventors of the tango tree, the first known competitive binary search tree data structure. Iacono obtained his M.S. at Stevens Institute of Technology and his Ph.D. in 2001 at Rutgers, the State University of New Jersey under the supervision of Michael Fredman. He is a Sloan Research Fellow and Fulbright Scholar. Formerly a professor of computer science in the New York University Tandon School of Engineering The New York University Tandon School of Engineering (commonly referred to as Tandon) is the engineering and applied sciences school of New York University. Tandon is the second oldest private engineering and technology school in the United Sta ..., he now works as a professor at the Université libre de Bruxelles. [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tango Tree
A tango tree is a type of binary search tree proposed by Erik D. Demaine, Dion Harmon, John Iacono, and Mihai Pătrașcu in 2004. It is named after Buenos Aires, of which the tango is emblematic. It is an online binary search tree that achieves an O(\log \log n) competitive ratio relative to the offline optimal binary search tree, while only using O(\log \log n) additional bits of memory per node. This improved upon the previous best known competitive ratio, which was O(\log n). Structure Tango trees work by partitioning a binary search tree into a set of ''preferred paths'', which are themselves stored in auxiliary trees (so the tango tree is represented as a tree of trees). Reference tree To construct a tango tree, we simulate a complete binary search tree called the ''reference tree'', which is simply a traditional binary search tree containing all the elements. This tree never shows up in the actual implementation, but is the conceptual basis behind the following pieces of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Open Problem
In science and mathematics, an open problem or an open question is a known problem which can be accurately stated, and which is assumed to have an objective and verifiable solution, but which has not yet been solved (i.e., no solution for it is known). In the history of science, some of these supposed open problems were "solved" by means of showing that they were not well-defined. In mathematics, many open problems are concerned with the question of whether a certain definition is or is not consistent. Two notable examples in mathematics that have been solved and ''closed'' by researchers in the late twentieth century are Fermat's Last Theorem and the four-color theorem.K. Appel and W. Haken (1977), "Every planar map is four colorable. Part I. Discharging", ''Illinois J. Math'' 21: 429–490. K. Appel, W. Haken, and J. Koch (1977), "Every planar map is four colorable. Part II. Reducibility", ''Illinois J. Math'' 21: 491–567. An important open mathematics problem solved i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Big O Notation
Big ''O'' notation is a mathematical notation that describes the limiting behavior of a function when the argument tends towards a particular value or infinity. Big O is a member of a family of notations invented by Paul Bachmann, Edmund Landau, and others, collectively called Bachmann–Landau notation or asymptotic notation. The letter O was chosen by Bachmann to stand for ''Ordnung'', meaning the order of approximation. In computer science, big O notation is used to classify algorithms according to how their run time or space requirements grow as the input size grows. In analytic number theory, big O notation is often used to express a bound on the difference between an arithmetical function and a better understood approximation; a famous example of such a difference is the remainder term in the prime number theorem. Big O notation is also used in many other fields to provide similar estimates. Big O notation characterizes functions according to their growth rates: d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
God's Algorithm
God's algorithm is a notion originating in discussions of ways to solve the Rubik's Cube puzzle, but which can also be applied to other combinatorial puzzles and mathematical games. It refers to any algorithm which produces a solution having the fewest possible moves. The allusion to the Deity is based on an assumption that only an omniscient being would know an optimal step from any given configuration. Scope Definition The notion applies to puzzles that can assume a finite number of "configurations", with a relatively small, well-defined arsenal of "moves" that may be applicable to configurations and then lead to a new configuration. Solving the puzzle means to reach a designated "final configuration", a singular configuration, or one of a collection of configurations. To solve the puzzle a sequence of moves is applied, starting from some arbitrary initial configuration. Solution An algorithm can be considered to solve such a puzzle if it takes as input an arbitrary initi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Pointer (computer Programming)
In computer science, a pointer is an object in many programming languages that stores a memory address. This can be that of another value located in computer memory, or in some cases, that of memory-mapped computer hardware. A pointer ''references'' a location in memory, and obtaining the value stored at that location is known as ''dereferencing'' the pointer. As an analogy, a page number in a book's index could be considered a pointer to the corresponding page; dereferencing such a pointer would be done by flipping to the page with the given page number and reading the text found on that page. The actual format and content of a pointer variable is dependent on the underlying computer architecture. Using pointers significantly improves performance for repetitive operations, like traversing iterable data structures (e.g. strings, lookup tables, control tables and tree structures). In particular, it is often much cheaper in time and space to copy and dereference pointers th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Erik Demaine
Erik D. Demaine (born February 28, 1981) is a professor of computer science at the Massachusetts Institute of Technology and a former child prodigy. Early life and education Demaine was born in Halifax, Nova Scotia, to artist sculptor Martin L. Demaine and Judy Anderson. From the age of 7, he was identified as a child prodigy and spent time traveling across North America with his father. He was home-schooled during that time span until entering university at the age of 12. Demaine completed his bachelor's degree at 14 years of age at Dalhousie University in Canada, and completed his PhD at the University of Waterloo by the time he was 20 years old. Demaine's PhD dissertation, a work in the field of computational origami, was completed at the University of Waterloo under the supervision of Anna Lubiw and Ian Munro. This work was awarded the Canadian Governor General's Gold Medal from the University of Waterloo and the NSERC Doctoral Prize (2003) for the best PhD thesis an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
