Results 1  10
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287,657
Autonomous units and their semantics  the sequential case
 ICGT 2006. LNCS
, 2006
"... In this paper, we introduce the notion of a community of autonomous units as a rulebased and graphtransformational device to model processes that run interactively but independently of each other in a common environment. The emphasis of the approach is laid on the study of the formal semantics of ..."
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Cited by 6 (6 self)
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of a community as a whole and of each of its member units separately. We concentrate on the sequential case where only one unit can act at a time and the rule applications of the involved units are interleaved with each other.
Maximum entropy markov models for information extraction and segmentation
, 2000
"... Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many textrelated tasks, such as partofspeech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled as multinomial ..."
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Cited by 561 (18 self)
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Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many textrelated tasks, such as partofspeech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled
Fast subsequence matching in timeseries databases
 PROCEEDINGS OF THE 1994 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA
, 1994
"... We present an efficient indexing method to locate 1dimensional subsequences within a collection of sequences, such that the subsequences match a given (query) pattern within a specified tolerance. The idea is to map each data sequence into a small set of multidimensional rectangles in feature space ..."
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Cited by 533 (24 self)
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such trails into subtrails, which are subsequently represented by their Minimum Bounding Rectangles (MBRs). We also examine queries of varying lengths, and we show how to handle each case efficiently. We implemented our method and carried out experiments on synthetic and real data (stock price movements). We
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
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Cited by 783 (29 self)
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of the weight vector in an associated feature space. The expansion coefficients are found by solving a quadratic programming problem, which we do by carrying out sequential optimization over pairs of input patterns. We also provide a preliminary theoretical analysis of the statistical performance of our
The Case for a SingleChip Multiprocessor
 IEEE Computer
, 1996
"... Advances in IC processing allow for more microprocessor design options. The increasing gate density and cost of wires in advanced integrated circuit technologies require that we look for new ways to use their capabilities effectively. This paper shows that in advanced technologies it is possible to ..."
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Cited by 440 (6 self)
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, the multiprocessor microarchitectnre outperforms the superscrdar architecture by a significant margin. Singlechip multiprocessor architectures have the advantage in that they offer localized implementation of a highclock rate processor for inherently sequential applications and low latency interprocessor
Sequential case series analysis for pharmacovigilance
 J. R. Stat. Soc. 2009
"... The selfcontrolled case series method is used to evaluate drug safety, particularly the safety of paediatric vaccines with respect to rare adverse reactions. We propose a group sequential version of the method for prospective surveillance of drug safety. Although the method is more widely applicab ..."
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Cited by 3 (0 self)
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The selfcontrolled case series method is used to evaluate drug safety, particularly the safety of paediatric vaccines with respect to rare adverse reactions. We propose a group sequential version of the method for prospective surveillance of drug safety. Although the method is more widely
CATH  a hierarchic classification of protein domain structures
 STRUCTURE
, 1997
"... Background: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structurebased classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function can ..."
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Cited by 470 (33 self)
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Background: Protein evolution gives rise to families of structurally related proteins, within which sequence identities can be extremely low. As a result, structurebased classifications can be effective at identifying unanticipated relationships in known structures and in optimal cases function
Convergence of Sequential Monte Carlo Methods
 SEQUENTIAL MONTE CARLO METHODS IN PRACTICE
, 2000
"... Bayesian estimation problems where the posterior distribution evolves over time through the accumulation of data arise in many applications in statistics and related fields. Recently, a large number of algorithms and applications based on sequential Monte Carlo methods (also known as particle filter ..."
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Cited by 243 (13 self)
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Bayesian estimation problems where the posterior distribution evolves over time through the accumulation of data arise in many applications in statistics and related fields. Recently, a large number of algorithms and applications based on sequential Monte Carlo methods (also known as particle
Morphological grayscale reconstruction in image analysis: Applications and efficient algorithms
 IEEE Transactions on Image Processing
, 1993
"... Morphological reconstruction is part of a set of image operators often referred to as geodesic. In the binary case, reconstruction simply extracts the connected components of a binary image I (the mask) which are \marked " by a (binary) image J contained in I. This transformation can be ext ..."
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Cited by 336 (3 self)
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Morphological reconstruction is part of a set of image operators often referred to as geodesic. In the binary case, reconstruction simply extracts the connected components of a binary image I (the mask) which are \marked " by a (binary) image J contained in I. This transformation can
Hierarchical classification of Web content
, 2000
"... sdumais @ microsoft.com This paper explores the use of hierarchical structure for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train different secondlevel classifiers. In the hierarchical case, a model is learned to distinguish a seco ..."
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Cited by 329 (4 self)
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sdumais @ microsoft.com This paper explores the use of hierarchical structure for classifying a large, heterogeneous collection of web content. The hierarchical structure is initially used to train different secondlevel classifiers. In the hierarchical case, a model is learned to distinguish a
Results 1  10
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287,657