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17,512
On the Use of Windows for Harmonic Analysis With the Discrete Fourier Transform
- Proc. IEEE
, 1978
"... Ahmw-This Pw!r mak = available a concise review of data win- compromise consists of applying windows to the sampled daws pad the ^ affect On the Of in the data set, or equivalently, smoothing the spectral samples. '7 of aoise9 m the ptesence of sdroag bar- The two operations to which we subject ..."
Abstract
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Cited by 668 (0 self)
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Ahmw-This Pw!r mak = available a concise review of data win- compromise consists of applying windows to the sampled daws pad the ^ affect On the Of in the data set, or equivalently, smoothing the spectral samples. '7 of aoise9 m the ptesence of sdroag bar- The two operations to which we
Universal Approximators for Discrete Data
, 2011
"... This report proofs that discriminative Restricted Boltzmann Machines (RBMs) are universal approximators for discrete data by adapting existing ..."
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This report proofs that discriminative Restricted Boltzmann Machines (RBMs) are universal approximators for discrete data by adapting existing
K.B.: Multi-Interval Discretization of Continuous-Valued Attributes for Classication Learning. In:
- IJCAI.
, 1993
"... Abstract Since most real-world applications of classification learning involve continuous-valued 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 continuous-valued a ..."
Abstract
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Cited by 832 (7 self)
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Abstract Since most real-world applications of classification learning involve continuous-valued 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 continuous
Management of multidimensional discrete data
- Very Large Databases Journal
, 1994
"... Abstract. Spatial database management involves two main categories of data: vector and raster data. The former has received a lot of in-depth investigation; the latter still lacks a sound framework. Current DBMSs either regard raster data as pure byte sequences where the DBMS has no knowledge about ..."
Abstract
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Cited by 29 (7 self)
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of multidimensional discrete data (MDD) in databases, including operations on arrays of arbitrary size over arbitrary data types. A set of requirements is developed, a small set of language constructs is proposed (based on a formal algebraic semantics), and a novel MDD architecture is outlined to provide the basis
Latent dirichlet allocation
- Journal of Machine Learning Research
, 2003
"... We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, ..."
Abstract
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Cited by 4365 (92 self)
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We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is
Mean shift: A robust approach toward feature space analysis
- In PAMI
, 2002
"... A general nonparametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure, the mean shift. We prove for discrete data the convergence ..."
Abstract
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Cited by 2395 (37 self)
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A general nonparametric technique is proposed for the analysis of a complex multimodal feature space and to delineate arbitrarily shaped clusters in it. The basic computational module of the technique is an old pattern recognition procedure, the mean shift. We prove for discrete data
An Introduction to the Kalman Filter
- UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
, 1995
"... In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area o ..."
Abstract
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Cited by 1146 (13 self)
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In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area
Projection Pursuit for Discrete Data
, 2008
"... This paper develops projection pursuit for discrete data using the discrete Radon transform. Discrete projection pursuit is presented as an exploratory method for finding informative low dimensional views of data such as binary vectors, rankings, phylogenetic trees or graphs. We show that for most ..."
Abstract
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Cited by 4 (2 self)
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This paper develops projection pursuit for discrete data using the discrete Radon transform. Discrete projection pursuit is presented as an exploratory method for finding informative low dimensional views of data such as binary vectors, rankings, phylogenetic trees or graphs. We show
Evidence evaluation for discrete data
"... Methods for the evaluation of evidence in the form of measurements by means of the likelihood ratio are becoming more widespread. There is a paucity of methods for the evaluation of evidence in the form of counts by means of the likelihood ratio. The outline of an empirical method based on relative ..."
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phonetics. There is discussion of the problems particular to the evaluation of evidence for discrete data, with suggestions for further work.
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