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142
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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, must not exceed n C . In other words, the reduction factor is bound by the number of coils used. Note that n P does not need to be the same for all partial unfolding steps. Upon noninteger reduction the number of pixels actually superimposed may vary in the reduced FOV. Generally, the degree
A general data reduction scheme for domination in graphs
 In Proc. 32nd SOFSEM, volume 3831 of LNCS
, 2006
"... Abstract. Data reduction by polynomialtime preprocessing is a core concept of (parameterized) complexity analysis in solving NPhard problems. Its practical usefulness is confirmed by experimental work. Here, generalizing and extending previous work, we present a set of data reduction preprocessing ..."
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Cited by 11 (3 self)
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Abstract. Data reduction by polynomialtime preprocessing is a core concept of (parameterized) complexity analysis in solving NPhard problems. Its practical usefulness is confirmed by experimental work. Here, generalizing and extending previous work, we present a set of data reduction
SeparatorBased Data Reduction for Signed Graph Balancing
 JOURNAL OF COMBINATORIAL OPTIMIZATION
, 2007
"... Polynomialtime data reduction is a classical approach to hard graph problems. Typically, particular small subgraphs are replaced by smaller gadgets. We generalize this approach to handle any small subgraph that has a small separator connecting it to the rest of the graph. The problem we study is th ..."
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Cited by 5 (0 self)
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data reductions, and can be applied to a large number of graph problems where a coloring or a subset of the vertices is sought. To solve the instances that remain after reduction, we use a fixedparameter algorithm based on iterative compression with a very effective heuristic speedup. Our
A PolynomialTime Algorithm for Memory Space Reduction
"... Reducing memoryspace requirement is important to many applications. For dataintensive applications, it may help avoid executing the program outofcore. For highperformance computing, memoryspace reduction may improve the cache hit rate as well as performance. For embedded systems, it can reduce t ..."
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fusion and array contraction to minimize the data memory required to execute a collection of multilevel loop nests. The integer programming problem is then reduced to an equivalent network flow problem which can be solved in polynomial time. Key words: compilers, optimization, graph theory, network flow
An O∗(2 n ) algorithm for graph coloring and other partitioning problems via inclusionexclusion
 IN PROCEEDINGS OF THE 47TH ANNUAL IEEE SYMPOSIUM ON FOUNDATIONS OF COMPUTER SCIENCE (FOCS 2006), IEEE
, 2006
"... We use the principle of inclusion and exclusion, combined with polynomial time segmentation and fast Möbius transform, to solve the generic problem of summing or optimizing over the partitions of n elements into a given number of weighted subsets. This problem subsumes various classical graph partit ..."
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Cited by 23 (1 self)
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We use the principle of inclusion and exclusion, combined with polynomial time segmentation and fast Möbius transform, to solve the generic problem of summing or optimizing over the partitions of n elements into a given number of weighted subsets. This problem subsumes various classical graph
Optimizing Array Distributions in DataParallel Programs
 Languages and Compilers for Parallel Computing, LNCS
, 1994
"... Data parallel programs are sensitive to the distribution of data across processor nodes. We formulate the reduction of internode communication as an optimization on a colored graph. We present a technique that records the run time internode communication caused by the movement of array data betwee ..."
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Cited by 3 (1 self)
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Data parallel programs are sensitive to the distribution of data across processor nodes. We formulate the reduction of internode communication as an optimization on a colored graph. We present a technique that records the run time internode communication caused by the movement of array data
A BicriteriaOptimizationApproachBased DimensionalityReduction Model for the Color Display of Hyperspectral Images
"... Abstract—This paper proposes a new nonlinear dimensionalityreduction model based on a bicriteria global optimization approach for the color display of hyperspectral images. The proposed fusion model is derived from two wellknown and contradictory criteria of good visualization, which are useful in ..."
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Cited by 3 (1 self)
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, color display model, complete graph, dimensionalityreduction model, FastMap optimization, local exploration search, low dimensional embedding, Metropolis algorithm, multicriteria optimization, multidimensional hyperspectral imagery, nonstationary Markov random field model, stress function. I.
Dense & Sparse Graph Partition
, 2010
"... In a graph G = (V, E), the density is the ratio between the number of edges E  and the number of vertices V . This criterion may be used to find communities in a graph: groups of highly connected vertices. We propose an optimization problem based on this criterion, the idea is to find the vertex ..."
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Cited by 1 (0 self)
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the vertex partition that maximizes the sum of the densities of each class. We prove that this problem is NPhard by giving a reduction from graphkcolorability. Additionally, we give a polynomial time algorithm for the special case of trees. 1
CONVEX OPTIMIZATION LEARNING OF FAITHFUL EUCLIDEAN DISTANCE REPRESENTATIONS IN NONLINEAR DIMENSIONALITY REDUCTION∗
"... Abstract. Classical multidimensional scaling only works well when the noisy distances observed in a high dimensional space can be faithfully represented by Euclidean distances in a low dimensional space. Advanced models such as Maximum Variance Unfolding (MVU) and Minimum Volume Embedding (MVE) use ..."
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. Numerical experiments show that the model can produce configurations of high quality on large data points that the SDP approach would struggle to cope with. Key words. Euclidean distance matrices, convex optimization, multidimensional scaling, nonlinear dimensionality reduction, lowrank matrices, error
More compact oracles for approximate distances in undirected planar graphs
 In SODA ’13
, 2013
"... Distance oracles are data structures that provide fast (possibly approximate) answers to shortestpath and distance queries in graphs. The tradeoff between the space requirements and the query time of distance oracles is of particular interest and the main focus of this paper. In FOCS‘01, Thorup int ..."
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Cited by 4 (2 self)
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: Õ(·) hides lowdegree polynomials in log(1/) and log∗(n).) ar X iv
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