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Inhomogeneity of the urelements in the usual models of NFU
, 2005
"... The simplest typed theory of sets is the multisorted first order system TST with equality and membership as primitive predicates and with sorts (types) indexed by the natural numbers. Atomic formulas are wellformed if they are of one of the forms x n ∈ y n+1; x n = y n. The axioms of TST are exten ..."
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The simplest typed theory of sets is the multisorted first order system TST with equality and membership as primitive predicates and with sorts (types) indexed by the natural numbers. Atomic formulas are wellformed if they are of one of the forms x n ∈ y n+1; x n = y n. The axioms of TST are extensionality (objects of positive type are equal iff they have the same members) and comprehension (“{x n  φ} n+1 exists ” for any formula φ in the language of TST). (this theory has often been incorrectly attributed to Russell, by this author among others: see [17] for a discussion of the actual history of this system). Quine’s New Foundations (NF) ([14]) is obtained from TST by abandoning the types but retaining the same axioms. Note that the comprehension axioms of NF are not all the axioms “{x  φ} exists ” for φ a formula in the language of NF: this would be the inconsistent comprehension axiom of naive set theory. The comprehension axioms of NF are those assertions “{x  φ} exists ” where φ can be obtained from a formula of TST by dropping distinctions of type between variables (without creating any additional identifications between variables).
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 554 (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
A subordinated stochastic process model with finite variance for speculative prices
 Econometrica
, 1973
"... Thanks are due to Hendrik Houthakker and Christopher Sims, for both encouragement and advice in developing this paper. As usual, all remaining errors are my own. This research was supported by a Harvard Dissertation Fellowship, NSF grant 33708, and the ..."
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Cited by 547 (1 self)
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Thanks are due to Hendrik Houthakker and Christopher Sims, for both encouragement and advice in developing this paper. As usual, all remaining errors are my own. This research was supported by a Harvard Dissertation Fellowship, NSF grant 33708, and the
An intrusiondetection model
 IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 1987
"... A model of a realtime intrusiondetection expert system capable of detecting breakins, penetrations, and other forms of computer abuse is described. The model is based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns of sy ..."
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Cited by 632 (0 self)
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A model of a realtime intrusiondetection expert system capable of detecting breakins, penetrations, and other forms of computer abuse is described. The model is based on the hypothesis that security violations can be detected by monitoring a system's audit records for abnormal patterns
Nonparametric model for background subtraction
 in ECCV ’00
, 2000
"... Abstract. Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel nonparametric background model and a background subtraction approach. The model can ..."
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Cited by 538 (17 self)
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Abstract. Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a novel nonparametric background model and a background subtraction approach. The model
Learning probabilistic relational models
 In IJCAI
, 1999
"... A large portion of realworld data is stored in commercial relational database systems. In contrast, most statistical learning methods work only with "flat " data representations. Thus, to apply these methods, we are forced to convert our data into a flat form, thereby losing much ..."
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Cited by 619 (31 self)
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of the relational structure present in our database. This paper builds on the recent work on probabilistic relational models (PRMs), and describes how to learn them from databases. PRMs allow the properties of an object to depend probabilistically both on other properties of that object and on properties of related
A Model of Investor Sentiment
 Journal of Financial Economics
, 1998
"... Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment, or ..."
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Cited by 743 (28 self)
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Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment
On active contour models and balloons
 CVGIP: Image
"... The use.of energyminimizing curves, known as “snakes, ” to extract features of interest in images has been introduced by Kass, Witkhr & Terzopoulos (Znt. J. Comput. Vision 1, 1987,321331). We present a model of deformation which solves some of the problems encountered with the original method. ..."
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Cited by 582 (43 self)
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The use.of energyminimizing curves, known as “snakes, ” to extract features of interest in images has been introduced by Kass, Witkhr & Terzopoulos (Znt. J. Comput. Vision 1, 1987,321331). We present a model of deformation which solves some of the problems encountered with the original method
An introduction to hidden Markov models
 IEEE ASSp Magazine
, 1986
"... The basic theory of Markov chains has been known to ..."
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Cited by 1110 (2 self)
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The basic theory of Markov chains has been known to
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