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Theoretical improvements in algorithmic efficiency for network flow problems

, 1972
"... This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps req ..."
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Cited by 560 (0 self)
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This paper presents new algorithms for the maximum flow problem, the Hitchcock transportation problem, and the general minimumcost flow problem. Upper bounds on ... the numbers of steps in these algorithms are derived, and are shown to compale favorably with upper bounds on the numbers of steps
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1996
"... We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum and c ..."
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Cited by 774 (20 self)
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We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum
Fast and robust fixedpoint algorithms for independent component analysis
 IEEE TRANS. NEURAL NETW
, 1999
"... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s informat ..."
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Cited by 884 (34 self)
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informationtheoretic approach and the projection pursuit approach. Using maximum entropy approximations of differential entropy, we introduce a family of new contrast (objective) functions for ICA. These contrast functions enable both the estimation of the whole decomposition by minimizing mutual information
K.B.: MultiInterval Discretization of ContinuousValued Attributes for Classication Learning. In:
 IJCAI.
, 1993
"... Abstract Since most realworld applications of classification learning involve continuousvalued attributes, properly addressing the discretization process is an important problem. This paper addresses the use of the entropy minimization heuristic for discretizing the range of a continuousvalued a ..."
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Cited by 832 (7 self)
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valued attribute into multiple intervals. We briefly present theoretical evidence for the appropriateness of this heuristic for use in the binary discretization algorithm used in ID3, C4, CART, and other learning algorithms. The results serve to justify extending the algorithm to derive multiple intervals. We
The role of deliberate practice in the acquisition of expert performance
 Psychological Review
, 1993
"... The theoretical framework presented in this article explains expert performance as the end result of individuals ' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen of ef ..."
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Cited by 690 (15 self)
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The theoretical framework presented in this article explains expert performance as the end result of individuals ' prolonged efforts to improve performance while negotiating motivational and external constraints. In most domains of expertise, individuals begin in their childhood a regimen
A Lattice Design to Reach the Theoretical Minimum Emittance for a Storage Ring.
"... The theoretical minimum emittance (TME) for a storage ring is given if both the horizontal betatron and the dispersion function have a minimum in the middle oft the bending magnet and furthermore meet special values. In most of the storage rings the emittance is a factor 2 to 5 higher as the TMEv ..."
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Cited by 1 (0 self)
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The theoretical minimum emittance (TME) for a storage ring is given if both the horizontal betatron and the dispersion function have a minimum in the middle oft the bending magnet and furthermore meet special values. In most of the storage rings the emittance is a factor 2 to 5 higher as the TME
Fast, singlemolecule localization that achieves theoretically minimum uncertainty
"... We describe an iterative algorithm that converges to the maximum likelihood estimate of the position and intensity of a single fluorophore. Our technique efficiently computes and achieves the CramérRao Lower Bound, an essential tool for parameter estimation. An implementation of the algorithm on gr ..."
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Cited by 3 (1 self)
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We describe an iterative algorithm that converges to the maximum likelihood estimate of the position and intensity of a single fluorophore. Our technique efficiently computes and achieves the CramérRao Lower Bound, an essential tool for parameter estimation. An implementation of the algorithm on graphics processing unit hardware achieves more than 105 combined fits and CramérRao Lower Bound calculations per second, enabling realtime data analysis for superresolution imaging and other applications. In many single molecule fluorescence applications, it is often desired to find the position and intensity of a single fluorophore as well as to estimate the accuracy and precision of these parameters. Where accuracy is a measure of the systematic error or bias and precision is a measure of the statistical error of an estimator1. In recent work that uses singlemolecule localization to generate superresolution images26, single emitters are located and on the mosaic of their found positions a twodimensional Gaussian profile is placed to generate the final superresolution images. The width of the placed Gaussian blob, σ, is given by the precision of the fluorophore position localization σ = (σ2x + σ2y)1/2 and in these superresolution techniques it is therefore necessary to both find the parameters and estimate their
Sparse signal reconstruction from limited data using FOCUSS: A reweighted minimum norm algorithm
 IEEE TRANS. SIGNAL PROCESSING
, 1997
"... We present a nonparametric algorithm for finding localized energy solutions from limited data. The problem we address is underdetermined, and no prior knowledge of the shape of the region on which the solution is nonzero is assumed. Termed the FOcal Underdetermined System Solver (FOCUSS), the algor ..."
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Cited by 368 (22 self)
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of the preceding iterative solutions. The algorithm is presented as a general estimation tool usable across different applications. A detailed analysis laying the theoretical foundation for the algorithm is given and includes proofs of global and local convergence and a derivation of the rate of convergence. A
An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1993
"... A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices. Cl ..."
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Cited by 360 (0 self)
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A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices
Minimum complexity density estimation
 IEEE TRANS. INF. THEORY
, 1991
"... The minimum complexity or minimum descriptionlength criterion developed by Kolmogorov, Rissanen, Wallace, So&in, and others leads to consistent probability density estimators. These density estimators are defined to achieve the best compromise between likelihood and simplicity. A related issue ..."
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Cited by 247 (8 self)
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The minimum complexity or minimum descriptionlength criterion developed by Kolmogorov, Rissanen, Wallace, So&in, and others leads to consistent probability density estimators. These density estimators are defined to achieve the best compromise between likelihood and simplicity. A related issue
Results 1  10
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4,384