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InformationTheoretic CoClustering
 In KDD
, 2003
"... Twodimensional contingency or cooccurrence tables arise frequently in important applications such as text, weblog and marketbasket data analysis. A basic problem in contingency table analysis is coclustering: simultaneous clustering of the rows and columns. A novel theoretical formulation views ..."
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Cited by 346 (12 self)
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Twodimensional contingency or cooccurrence tables arise frequently in important applications such as text, weblog and marketbasket data analysis. A basic problem in contingency table analysis is coclustering: simultaneous clustering of the rows and columns. A novel theoretical formulation
Edge Detection and Ridge Detection with Automatic Scale Selection
 CVPR'96
, 1996
"... When extracting features from image data, the type of information that can be extracted may be strongly dependent on the scales at which the feature detectors are applied. This article presents a systematic methodology for addressing this problem. A mechanism is presented for automatic selection of ..."
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Cited by 347 (24 self)
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of the strength of the edge response is locally maximal over scales. An important property of this definition is that it allows the scale levels to vary along the edge. Two specific measures of edge strength are analysed in detail. It is shown that by expressing these in terms of &
The EM Algorithm for Mixtures of Factor Analyzers
, 1997
"... Factor analysis, a statistical method for modeling the covariance structure of high dimensional data using a small number of latent variables, can be extended by allowing different local factor models in different regions of the input space. This results in a model which concurrently performs cluste ..."
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Cited by 278 (18 self)
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clustering and dimensionality reduction, and can be thought of as a reduced dimension mixture of Gaussians. We present an exact ExpectationMaximization algorithm for fitting the parameters of this mixture of factor analyzers. 1 Introduction Clustering and dimensionality reduction have long been considered
Feature Selection via Concave Minimization and Support Vector Machines
 Machine Learning Proceedings of the Fifteenth International Conference(ICML ’98
, 1998
"... Computational comparison is made between two feature selection approaches for finding a separating plane that discriminates between two point sets in an ndimensional feature space that utilizes as few of the n features (dimensions) as possible. In the concave minimization approach [19, 5] a separat ..."
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Cited by 263 (23 self)
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Computational comparison is made between two feature selection approaches for finding a separating plane that discriminates between two point sets in an ndimensional feature space that utilizes as few of the n features (dimensions) as possible. In the concave minimization approach [19, 5] a
Principles of Object Perception
 Cognitive Science
, 1990
"... Research on human infants has begun to shed light on earlydevelpping processes for segmenting perceptual arrays into objects. Infants appear to perceive objects by analyzing threedimensional surface arrangements and motions. Their perception does not accord with a general tendency to maximize fig ..."
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Cited by 259 (6 self)
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Research on human infants has begun to shed light on earlydevelpping processes for segmenting perceptual arrays into objects. Infants appear to perceive objects by analyzing threedimensional surface arrangements and motions. Their perception does not accord with a general tendency to maximize
TwoDimensional Interleaving Schemes with Repetitions
 IBM Research Report RJ 10047
, 1996
"... We present 2dimensional interleaving schemes, with repetition, for correcting 2dimensional bursts (or clusters) of errors, where a cluster of errors is characterized by its area. A recent application of correction of 2dimensional clusters appeared in the context of holographic storage. Known in ..."
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Cited by 9 (5 self)
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We present 2dimensional interleaving schemes, with repetition, for correcting 2dimensional bursts (or clusters) of errors, where a cluster of errors is characterized by its area. A recent application of correction of 2dimensional clusters appeared in the context of holographic storage. Known
On Maximal Repetitions in Words
 J. Discrete Algorithms
, 1999
"... A (fractional) repetition in a word w is a subword with the period of at most half of the subword length. We study maximal repetitions occurring in w, that is those for which any extended subword of w has a bigger period. The set of such repetitions represents in a compact way all repetitions in w. ..."
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Cited by 56 (6 self)
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A (fractional) repetition in a word w is a subword with the period of at most half of the subword length. We study maximal repetitions occurring in w, that is those for which any extended subword of w has a bigger period. The set of such repetitions represents in a compact way all repetitions in w
Twodimensional arrays with maximal complexity
, 2006
"... We present natural bounds for the complexity function of twodimensional arrays, and we study the shape of the maximal complexity function. Some problems concerning the existence of maximal arrays are discussed. ..."
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Cited by 2 (0 self)
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We present natural bounds for the complexity function of twodimensional arrays, and we study the shape of the maximal complexity function. Some problems concerning the existence of maximal arrays are discussed.
Supervised learning from incomplete data via an EM approach
 Advances in Neural Information Processing Systems 6
, 1994
"... Realworld learning tasks may involve highdimensional data sets with arbitrary patterns of missing data. In this paper we present a framework based on maximum likelihood density estimation for learning from such data sets. We use mixture models for the density estimates and make two distinct appeal ..."
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Cited by 232 (2 self)
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Realworld learning tasks may involve highdimensional data sets with arbitrary patterns of missing data. In this paper we present a framework based on maximum likelihood density estimation for learning from such data sets. We use mixture models for the density estimates and make two distinct
The TwoDimensional
, 1952
"... A solution is developed in implicit form for the problem of assigning h r men to n iobs, the proportion of men to be assigned to each]ob being specified in advance. Suppose that it is desired to assign N men to n jobs, the proportion of men to be assigned to each job being specified in advance. It i ..."
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. It is desired to maximize the average weighted productivity of the men, the productivity of each man being weighted according to the importance of the job to which he is assigned. It is assumed that the productivity of each man for each job is known in advance and caa be used as a basis for assignment. If x
Results 1  10
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