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Inductive learning algorithms and representations for text categorization,”
 in Proceedings of the International Conference on Information and Knowledge Management,
, 1998
"... ABSTRACT Text categorization the assignment of natural language texts to one or more predefined categories based on their content is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text ..."
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Cited by 652 (8 self)
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ABSTRACT Text categorization the assignment of natural language texts to one or more predefined categories based on their content is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text
A theory for multiresolution signal decomposition : the wavelet representation
 IEEE Transaction on Pattern Analysis and Machine Intelligence
, 1989
"... AbstractMultiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolutions ..."
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Cited by 3538 (12 self)
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AbstractMultiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolutions
Advances in Prospect Theory: Cumulative Representation of Uncertainty
 JOURNAL OF RISK AND UNCERTAINTY, 5:297323 (1992)
, 1992
"... We develop a new version of prospect theory that employs cumulative rather than separable decision weights and extends the theory in several respects. This version, called cumulative prospect theory, applies to uncertain as well as to risky prospects with any number of outcomes, and it allows differ ..."
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Cited by 1717 (17 self)
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different weighting functions for gains and for losses. Two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting functions. A review of the experimental evidence and the results of a new experiment confirm a
Dynamic Bayesian Networks: Representation, Inference and Learning
, 2002
"... Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and biosequence analysis, and KFMs have bee ..."
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Cited by 770 (3 self)
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random variable. DBNs generalize KFMs by allowing arbitrary probability distributions, not just (unimodal) linearGaussian. In this thesis, I will discuss how to represent many different kinds of models as DBNs, how to perform exact and approximate inference in DBNs, and how to learn DBN models from
An axiomatization of the ratio/difference representation
 Journal of Mathematical Psychology
, 1983
"... If>, and>d are two quaternary relations on an arbitrary set A, a ratio/difference representation for>, and ad is defined to be a function f that represents 2, as an ordering of numerical ratios and ad as an ordering of numerical differences. Krantz, Lute, Suppes and Tversky (1971, Foundatio ..."
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Cited by 4 (0 self)
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If>, and>d are two quaternary relations on an arbitrary set A, a ratio/difference representation for>, and ad is defined to be a function f that represents 2, as an ordering of numerical ratios and ad as an ordering of numerical differences. Krantz, Lute, Suppes and Tversky (1971
Stable recovery of sparse overcomplete representations in the presence of noise
 IEEE TRANS. INFORM. THEORY
, 2006
"... Overcomplete representations are attracting interest in signal processing theory, particularly due to their potential to generate sparse representations of signals. However, in general, the problem of finding sparse representations must be unstable in the presence of noise. This paper establishes t ..."
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Cited by 460 (22 self)
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Overcomplete representations are attracting interest in signal processing theory, particularly due to their potential to generate sparse representations of signals. However, in general, the problem of finding sparse representations must be unstable in the presence of noise. This paper establishes
different representations in Grammatical Evolution
"... Abstract. Grammatical evolution (GE) is a form of grammarbased genetic programming. A particular feature of GE is that it adopts a distinction between the genotype and phenotype similar to that which exists in nature by using a grammar to map between the genotype and phenotype. This study seeks to ..."
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Cited by 2 (0 self)
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to extend our understanding of GE by examining the impact of different genotypic representations in order to determine whether certain representations, and associated diversitygeneration operators, improve GE’s efficiency and effectiveness. Four mutation operators using two different representations
Why a diagram is (sometimes) worth ten thousand words
 Cognitive Science
, 1987
"... We distinguish diagrammatic from sentential paperandpencil representationsof information by developing alternative models of informationprocessing systems that are informationally equivalent and that can be characterized as sentential or diagrammatic. Sentential representations are sequential, li ..."
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Cited by 804 (2 self)
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. Two sets of operators may differ in their copobilities for recognizing patterns, in the inferences they con carry out directly, and in their control strategies (in portitular. the control of search). Diogrommotic ond sentential representations sup
Different representations of Euclidean geometry
, 2008
"... Three different representation of the proper Euclidean geometry are considered. They differ in the number of basic elements, from which the geometrical objects are constructed. In Erepresentation there are three basic elements (point, segment, angle) and no additional structures. Vrepresentation c ..."
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Three different representation of the proper Euclidean geometry are considered. They differ in the number of basic elements, from which the geometrical objects are constructed. In Erepresentation there are three basic elements (point, segment, angle) and no additional structures. Vrepresentation
An InformationTheoretic Definition of Similarity
 In Proceedings of the 15th International Conference on Machine Learning
, 1998
"... Similarity is an important and widely used concept. Previous definitions of similarity are tied to a particular application or a form of knowledge representation. We present an informationtheoretic definition of similarity that is applicable as long as there is a probabilistic model. We demonstrate ..."
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Cited by 1243 (0 self)
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Similarity is an important and widely used concept. Previous definitions of similarity are tied to a particular application or a form of knowledge representation. We present an informationtheoretic definition of similarity that is applicable as long as there is a probabilistic model. We demonstrate
Results 1  10
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