Results 1 - 10 of 49,599

Constant-Time Quantum Algorithm For The Unstructured Search Problem

by Ahmed Younes , 2008
"... Given an item and a list of values of size N. It is required to decide if such item exists in the list. Classical computer can search for the item in O(N). The best known quantum algorithm can do the job in O ( √ N). In this paper, a quantum algorithm will be proposed that can search an unstructure ..."
Abstract - Add to MetaCart
Given an item and a list of values of size N. It is required to decide if such item exists in the list. Classical computer can search for the item in O(N). The best known quantum algorithm can do the job in O ( √ N). In this paper, a quantum algorithm will be proposed that can search

Search and replication in unstructured peer-to-peer networks

by Qin Lv, Pei Cao, Edith Cohen, Kai Li, Scott Shenker , 2002
"... Abstract Decentralized and unstructured peer-to-peer networks such as Gnutella are attractive for certain applicationsbecause they require no centralized directories and no precise control over network topologies and data placement. However, the flooding-based query algorithm used in Gnutella does n ..."
Abstract - Cited by 692 (6 self) - Add to MetaCart
Abstract Decentralized and unstructured peer-to-peer networks such as Gnutella are attractive for certain applicationsbecause they require no centralized directories and no precise control over network topologies and data placement. However, the flooding-based query algorithm used in Gnutella does

TABU SEARCH

by Fred Glover, Rafael Marti
"... Tabu Search is a metaheuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates a more flexible search behavior. Memory based strategies are therefore the hallm ..."
Abstract - Cited by 822 (48 self) - Add to MetaCart
the hallmark of tabu search approaches, founded on a quest for "integrating principles, " by which alternative forms of memory are appropriately combined with effective strategies for exploiting them. In this chapter we address the problem of training multilayer feed-forward neural networks

Tabu Search -- Part I

by Fred Glover , 1989
"... This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning, and more ..."
Abstract - Cited by 680 (11 self) - Add to MetaCart
This paper presents the fundamental principles underlying tabu search as a strategy for combinatorial optimization problems. Tabu search has achieved impressive practical successes in applications ranging from scheduling and computer channel balancing to cluster analysis and space planning

Greedy Randomized Adaptive Search Procedures

by Mauricio G. C. Resende , Celso C. Ribeiro , 2002
"... GRASP is a multi-start metaheuristic for combinatorial problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search phas ..."
Abstract - Cited by 647 (82 self) - Add to MetaCart
GRASP is a multi-start metaheuristic for combinatorial problems, in which each iteration consists basically of two phases: construction and local search. The construction phase builds a feasible solution, whose neighborhood is investigated until a local minimum is found during the local search

Pushing the Envelope: Planning, Propositional Logic, and Stochastic Search

by Henry Kautz, Bart Selman , 1996
"... Planning is a notoriously hard combinatorial search problem. In many interesting domains, current planning algorithms fail to scale up gracefully. By combining a general, stochastic search algorithm and appropriate problem encodings based on propositional logic, we are able to solve hard planning pr ..."
Abstract - Cited by 579 (33 self) - Add to MetaCart
Planning is a notoriously hard combinatorial search problem. In many interesting domains, current planning algorithms fail to scale up gracefully. By combining a general, stochastic search algorithm and appropriate problem encodings based on propositional logic, we are able to solve hard planning

Depth first search and linear graph algorithms

by Robert Tarjan - SIAM JOURNAL ON COMPUTING , 1972
"... The value of depth-first search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components of an undirect ..."
Abstract - Cited by 1406 (19 self) - Add to MetaCart
The value of depth-first search or "backtracking" as a technique for solving problems is illustrated by two examples. An improved version of an algorithm for finding the strongly connected components of a directed graph and ar algorithm for finding the biconnected components

Similarity search in high dimensions via hashing

by Aristides Gionis, Piotr Indyk, Rajeev Motwani , 1999
"... The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over high-dimensional data, e.g., image dat ..."
Abstract - Cited by 641 (10 self) - Add to MetaCart
The nearest- or near-neighbor query problems arise in a large variety of database applications, usually in the context of similarity searching. Of late, there has been increasing interest in building search/index structures for performing similarity search over high-dimensional data, e.g., image

Where the REALLY Hard Problems Are

by Peter Cheeseman, Bob Kanefsky, William M. Taylor - IN J. MYLOPOULOS AND R. REITER (EDS.), PROCEEDINGS OF 12TH INTERNATIONAL JOINT CONFERENCE ON AI (IJCAI-91),VOLUME 1 , 1991
"... It is well known that for many NP-complete problems, such as K-Sat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NP-complete problems can be summarized by at least one "order parameter", and that the hard p ..."
Abstract - Cited by 683 (1 self) - Add to MetaCart
It is well known that for many NP-complete problems, such as K-Sat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NP-complete problems can be summarized by at least one "order parameter", and that the hard

The anatomy of a large-scale hypertextual web search engine.

by Sergey Brin , Lawrence Page - Comput. Netw. ISDN Syst., , 1998
"... Abstract In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a fu ..."
Abstract - Cited by 4673 (5 self) - Add to MetaCart
an in-depth description of our large-scale web search engine --the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information
Results 1 - 10 of 49,599