Results 1 - 10 of 18,097

Synchronous data flow

by Edward A. Lee, et al. , 1987
"... Data flow is a natural paradigm for describing DSP applications for concurrent implementation on parallel hardware. Data flow programs for signal processing are directed graphs where each node represents a function and each arc represents a signal path. Synchronous data flow (SDF) is a special case ..."
Abstract - Cited by 622 (45 self) - Add to MetaCart
Data flow is a natural paradigm for describing DSP applications for concurrent implementation on parallel hardware. Data flow programs for signal processing are directed graphs where each node represents a function and each arc represents a signal path. Synchronous data flow (SDF) is a special case

Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning

by Richard S. Sutton , Doina Precup , Satinder Singh , 1999
"... Learning, planning, and representing knowledge at multiple levels of temporal abstraction are key, longstanding challenges for AI. In this paper we consider how these challenges can be addressed within the mathematical framework of reinforcement learning and Markov decision processes (MDPs). We exte ..."
Abstract - Cited by 569 (38 self) - Add to MetaCart
extend the usual notion of action in this framework to include options|closed-loop policies for taking action over a period of time. Examples of options include picking up an object, going to lunch, and traveling to a distant city, as well as primitive actions such as muscle twitches and joint knowledge

How bad is selfish routing?

by Tim Roughgarden, Éva Tardos - JOURNAL OF THE ACM , 2002
"... We consider the problem of routing traffic to optimize the performance of a congested network. We are given a network, a rate of traffic between each pair of nodes, and a latency function for each edge specifying the time needed to traverse the edge given its congestion; the objective is to route t ..."
Abstract - Cited by 657 (27 self) - Add to MetaCart
traffic such that the sum of all travel times—the total latency—is minimized. In many settings, it may be expensive or impossible to regulate network traffic so as to implement an optimal assignment of routes. In the absence of regulation by some central authority, we assume that each network user routes

Strongly Elliptic Systems and Boundary Integral Equations

by William Mclean , To Meg , 2000
"... Partial differential equations provide mathematical models of many important problems in the physical sciences and engineering. This book treats one class of such equations, concentrating on methods involving the use of surface potentials. It provides the first detailed exposition of the mathematic ..."
Abstract - Cited by 501 (0 self) - Add to MetaCart
or appropriate. Information regarding prices, travel timetables, and other factual information given in this work is correct at the time of first printing but Cambridge University Press does not guarantee the accuracy of such information thereafter. Cambridge University Press 978-0-521-66332-8 -Strongly Elliptic

Clustering by passing messages between data points

by Brendan J. Frey, Delbert Dueck - Science , 2007
"... Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initi ..."
Abstract - Cited by 696 (8 self) - Add to MetaCart
. We used affinity propagation to cluster images of faces, detect genes in microarray data, identify representative sentences in this manuscript, and identify cities that are efficiently accessed by airline travel. Affinity propagation found clusters with much lower error than other methods, and it did

Fusion, Propagation, and Structuring in Belief Networks

by Judea Pearl - ARTIFICIAL INTELLIGENCE , 1986
"... Belief networks are directed acyclic graphs in which the nodes represent propositions (or variables), the arcs signify direct dependencies between the linked propositions, and the strengths of these dependencies are quantified by conditional probabilities. A network of this sort can be used to repre ..."
Abstract - Cited by 484 (8 self) - Add to MetaCart
Belief networks are directed acyclic graphs in which the nodes represent propositions (or variables), the arcs signify direct dependencies between the linked propositions, and the strengths of these dependencies are quantified by conditional probabilities. A network of this sort can be used

Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems

by Sanjeev Arora - Journal of the ACM , 1998
"... Abstract. We present a polynomial time approximation scheme for Euclidean TSP in fixed dimensions. For every fixed c Ͼ 1 and given any n nodes in 2 , a randomized version of the scheme finds a (1 ϩ 1/c)-approximation to the optimum traveling salesman tour in O(n(log n) O(c) ) time. When the nodes ..."
Abstract - Cited by 397 (2 self) - Add to MetaCart
Abstract. We present a polynomial time approximation scheme for Euclidean TSP in fixed dimensions. For every fixed c Ͼ 1 and given any n nodes in 2 , a randomized version of the scheme finds a (1 ϩ 1/c)-approximation to the optimum traveling salesman tour in O(n(log n) O(c) ) time. When the nodes

A simple parallel algorithm for the maximal independent set problem

by Michael Luby - SIAM Journal on Computing , 1986
"... Simple parallel algorithms for the maximal independent set (MIS) problem are presented. The first algorithm is a Monte Carlo algorithm with a very local property. The local property of this algorithm may make it a useful protocol design tool in distributed computing environments and artificial intel ..."
Abstract - Cited by 450 (9 self) - Add to MetaCart
intelligence. One of the main contributions of this paper is the development of powerful and general technicjues for converting Monte Carlo algorithms into deterministic algorithms. These techniques arc used to convert the Monte Carlo algorithm for the MIS problem into a simple deterministic algorithm

A general approximation technique for constrained forest problems

by Michel X. Goemans, David P. Williamson - SIAM J. COMPUT. , 1995
"... We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph with trees, cycles, or paths satisfying certain requirements. In particular, many basic combinatorial optimization proble ..."
Abstract - Cited by 414 (21 self) - Add to MetaCart
problems fit in this framework, including the shortest path, minimum-cost spanning tree, minimum-weight perfect matching, traveling salesman, and Steiner tree problems. Our technique produces approximation algorithms that run in O(n log n) time and come within a factor of 2 of optimal for most

P-Complete Approximation Problems

by SARTAJ SAHNI , TEOFILO GONZALEZ , 1976
"... For P-complete problems such as traveling salesperson, cycle covers, 0-1 integer programming, multicommodity network flows, quadratic assignment, etc, it is shown that the approximation problem is also P-complete In contrast with these results, a linear time approximation algorithm for the clusterin ..."
Abstract - Cited by 376 (0 self) - Add to MetaCart
For P-complete problems such as traveling salesperson, cycle covers, 0-1 integer programming, multicommodity network flows, quadratic assignment, etc, it is shown that the approximation problem is also P-complete In contrast with these results, a linear time approximation algorithm
Results 1 - 10 of 18,097