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Degree Fluctuations and the Convergence Time of Consensus Algorithms
, 2012
"... We consider a consensus algorithm in which every node in a sequence of undirected, Bconnected graphs assigns equal weight to each of its neighbors. Under the assumption that the degree of each node is fixed (except for times when the node has no connections to other nodes), we show that consensus i ..."
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Cited by 5 (0 self)
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We consider a consensus algorithm in which every node in a sequence of undirected, Bconnected graphs assigns equal weight to each of its neighbors. Under the assumption that the degree of each node is fixed (except for times when the node has no connections to other nodes), we show that consensus
1Degree Fluctuations and the Convergence Time of Consensus Algorithms
"... We consider a consensus algorithm in which every node in a sequence of undirected, Bconnected graphs assigns equal weight to each of its neighbors. Under the assumption that the degree of each node is fixed (except for times when the node has no connections to other nodes), we show that consensus i ..."
Abstract
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We consider a consensus algorithm in which every node in a sequence of undirected, Bconnected graphs assigns equal weight to each of its neighbors. Under the assumption that the degree of each node is fixed (except for times when the node has no connections to other nodes), we show that consensus
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
Reopening the Convergence Debate: A new look at crosscountry growth empirics
 JOURNAL OF ECONOMIC GROWTH
, 1996
"... ..."
Time Discounting and Time Preference: A Critical Review
 Journal of Economic Literature
, 2002
"... www.people.cornell.edu/pages/edo1/. ..."
A learning algorithm for Boltzmann machines
 Cognitive Science
, 1985
"... The computotionol power of massively parallel networks of simple processing elements resides in the communication bandwidth provided by the hardware connections between elements. These connections con allow a significant fraction of the knowledge of the system to be applied to an instance of a probl ..."
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Cited by 586 (13 self)
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problem in o very short time. One kind of computation for which massively porollel networks appear to be well suited is large constraint satisfaction searches, but to use the connections efficiently two conditions must be met: First, a search technique that is suitable for parallel networks must be found
The Unix TimeSharing System
 Communications of the ACM
, 1974
"... Unix is a generalpurpose, multiuser, interactive operating system for the larger Digital Equipment Corporation PDP11 and the Interdata 8/32 computers. It offers a number of features seldom found even in larger operating systems, including i A hierarchical file system incorporating demountable vol ..."
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Cited by 536 (14 self)
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volumes, ii Compatible file, device, and interprocess I/O, iii The ability to initiate asynchronous processes, iv System command language selectable on a peruser basis, v Over 100 subsystems including a dozen languages, vi High degree of portability. This paper discusses the nature and implementation
Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms
 Evolutionary Computation
, 1994
"... In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands the user to have knowledge about t ..."
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Cited by 524 (4 self)
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the underlying problem. Moreover, in solving multiobjective problems, designers may be interested in a set of Paretooptimal points, instead of a single point. Since genetic algorithms(GAs) work with a population of points, it seems natural to use GAs in multiobjective optimization problems to capture a
LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
 ACM Trans. Math. Software
, 1982
"... An iterative method is given for solving Ax ~ffi b and minU Ax b 112, where the matrix A is large and sparse. The method is based on the bidiagonalization procedure of Golub and Kahan. It is analytically equivalent to the standard method of conjugate gradients, but possesses more favorable numerica ..."
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Cited by 649 (21 self)
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gradient algorithms, indicating that I~QR is the most reliable algorithm when A is illconditioned. Categories and Subject Descriptors: G.1.2 [Numerical Analysis]: ApprorJmationleast squares approximation; G.1.3 [Numerical Analysis]: Numerical Linear Algebralinear systems (direct and
Delayed internet routing convergence
 ACM SIGCOMM Computer Communication Review
, 2000
"... Abstractâ€”This paper examines the latency in Internet path failure, failover, and repair due to the convergence properties of interdomain routing. Unlike circuitswitched paths which exhibit failover on the order of milliseconds, our experimental measurements show that interdomain routers in the pac ..."
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Cited by 414 (5 self)
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Abstractâ€”This paper examines the latency in Internet path failure, failover, and repair due to the convergence properties of interdomain routing. Unlike circuitswitched paths which exhibit failover on the order of milliseconds, our experimental measurements show that interdomain routers
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284,898