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Maximum likelihood from incomplete data via the EM algorithm

by A. P. Dempster, N. M. Laird, D. B. Rubin - JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B , 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
Abstract - Cited by 11972 (17 self) - Add to MetaCart
A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value

Implementing Iterative Algorithms with SPARQL

by Robert W. Techentin, Barry K. Gilbert, Adam Lugowski Kevin, Deweese John Gilbert, Eric Dull, Mike Hinchey, Steven P. Reinhardt
"... The SPARQL declarative query language includes innovative capabilities to match subgraph patterns within a semantic graph database, providing a powerful base upon which to implement complex graph algorithms for very large data. Iterative algorithms are useful in a wide variety of domains, in particu ..."
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The SPARQL declarative query language includes innovative capabilities to match subgraph patterns within a semantic graph database, providing a powerful base upon which to implement complex graph algorithms for very large data. Iterative algorithms are useful in a wide variety of domains

Randomized registers and iterative algorithms

by Hyunyoung Lee, Jennifer L. Welch - Distributed Computing , 2005
"... We present three different specifications of a read-write register that may occasionally return out-of-date values — namely, a (basic) random register, a P-random register, and a monotone random register. We show that these specifications are implemented by the probabilistic quorum algorithm of Malk ..."
Abstract - Cited by 6 (1 self) - Add to MetaCart
of Malkhi, Reiter, Wool, and Wright, and we illustrate how to program with such registers in the framework of Bertsekas, using the notation of Üresin and Dubois. Consequently, existing iterative algorithms for a significant class of problems (including solving systems of linear equations, finding shortest

ITERATIVE ALGORITHMS FOR MULTICHANNEL EQUALIZATION

by unknown authors
"... A fast iterative algorithm, with computation based on the fast Fourier transform (FFT), is presented. It can be used to control a soundfield at several control points with a loudspeaker array from multiple reference signals. It designs an equalizer able to invert long FIR filters and which achieves ..."
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A fast iterative algorithm, with computation based on the fast Fourier transform (FFT), is presented. It can be used to control a soundfield at several control points with a loudspeaker array from multiple reference signals. It designs an equalizer able to invert long FIR filters and which achieves

An iterative algorithm for synthesizing invariants

by Jussi Rintanen - In Proc. 17th National Conference on Artificial Intelligence (AAAI’00), 806
"... We present a general algorithm for synthesizing state invariants that speed up automated planners and have other applications in reasoning about change. Invariants are facts that hold in all states that are reachable from an initial state by the application of a number of operators. In contrast to e ..."
Abstract - Cited by 49 (2 self) - Add to MetaCart
We present a general algorithm for synthesizing state invariants that speed up automated planners and have other applications in reasoning about change. Invariants are facts that hold in all states that are reachable from an initial state by the application of a number of operators. In contrast

Feedback in Iterative Algorithms

by Charles Byrne (charles , 2005
"... When the nonnegative system of linear equations y = Px has no non-negative exact solutions, block-iterative methods fail to converge, exhibiting, instead, subsequential convergence leading to a limit cycle of two or more dis-tinct vectors. From the vectors of the limit cycle we extract new data, rep ..."
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approach: Can we show the existence of limit cycles for these other block-iterative algorithms? Does the sequence of successive limit cycles converge to a single vector? If so, which vector is it? 1

Iterative Algorithms for Graphical Models

by Robert Mateescu , 2003
"... Probabilistic inference in Bayesian networks, and even reasoning within error bounds are known to be NP-hard problems. Our research focuses on investigating approximate message-passing algorithms inspired by Pearl's belief propagation algorithm and by variable elimination. We study the advantag ..."
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the advantages of bounded inference provided by anytime schemes such as Mini-Clustering (MC), and combine them with the virtues of iterative algorithms such as Iterative Belief Propagation (IBP). Our resulting hybrid algorithm Iterative Join-Graph Propagation (IJGP) is shown empirically to surpass

A fast iterative shrinkage-thresholding algorithm with application to . . .

by Amir Beck, Marc Teboulle , 2009
"... We consider the class of Iterative Shrinkage-Thresholding Algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods is attractive due to its simplicity, however, they are also known to converge quite slowly. In this paper we present a Fast Iterat ..."
Abstract - Cited by 1058 (9 self) - Add to MetaCart
We consider the class of Iterative Shrinkage-Thresholding Algorithms (ISTA) for solving linear inverse problems arising in signal/image processing. This class of methods is attractive due to its simplicity, however, they are also known to converge quite slowly. In this paper we present a Fast

Iterative algorithm · Sparse algorithm

by Yun Chi, Shenghuo Zhu, Y. Chi, S. Zhu
"... FacetCube: a general framework for non-negative tensor factorization ..."
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FacetCube: a general framework for non-negative tensor factorization

Gaussian elimination as an iterative algorithm

by Alex Townsend, Lloyd N. Trefethen - SIAM News , 2013
"... Gaussian elimination for solving an n × n linear system of equations Ax = b is the archetypal direct method of numerical linear algebra. In this note we point out that GE has an iterative side too. We can’t resist beginning with a curious piece of history. The second most famous algorithm of numeric ..."
Abstract - Cited by 3 (3 self) - Add to MetaCart
Gaussian elimination for solving an n × n linear system of equations Ax = b is the archetypal direct method of numerical linear algebra. In this note we point out that GE has an iterative side too. We can’t resist beginning with a curious piece of history. The second most famous algorithm
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