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Results 1 - 10
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353,819
Maximum likelihood from incomplete data via the EM algorithm
- JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
Abstract
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Cited by 11972 (17 self)
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A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value
Social force model for pedestrian dynamics
- Physical Review E
, 1995
"... It is suggested that the motion of pedestrians can be described as if they would be subject to ‘social forces’. These ‘forces ’ are not directly exerted by the pedestrians ’ personal environment, but they are a measure for the internal motivations of the individuals to perform certain actions (movem ..."
Abstract
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Cited by 504 (25 self)
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(movements). The corresponding force concept is discussed in more detail and can be also applied to the description of other behaviors. In the presented model of pedestrian behavior several force terms are essential: First, a term describing the acceleration towards the desired velocity of motion. Second
Improved Statistical Alignment Models
- In Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics
, 2000
"... In this paper, we present and compare various single-word based alignment models for statistical machine translation. We discuss the five IBM alignment models, the Hidden-Markov alignment model, smoothing techniques and various modifications. ..."
Abstract
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Cited by 607 (12 self)
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In this paper, we present and compare various single-word based alignment models for statistical machine translation. We discuss the five IBM alignment models, the Hidden-Markov alignment model, smoothing techniques and various modifications.
Learning in graphical models
- STATISTICAL SCIENCE
, 2004
"... Statistical applications in fields such as bioinformatics, information retrieval, speech processing, image processing and communications often involve large-scale models in which thousands or millions of random variables are linked in complex ways. Graphical models provide a general methodology for ..."
Abstract
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Cited by 806 (10 self)
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-scale data analysis problems. We also present examples of graphical models in bioinformatics, error-control coding and language processing.
Learning probabilistic relational models
- In IJCAI
, 1999
"... A large portion of real-world 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 ..."
Abstract
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Cited by 613 (30 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 ..."
Abstract
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Cited by 777 (32 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
Compositional Model Checking
, 1999
"... We describe a method for reducing the complexity of temporal logic model checking in systems composed of many parallel processes. The goal is to check properties of the components of a system and then deduce global properties from these local properties. The main difficulty with this type of approac ..."
Abstract
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Cited by 3252 (70 self)
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of approach is that local properties are often not preserved at the global level. We present a general framework for using additional interface processes to model the environment for a component. These interface processes are typically much simpler than the full environment of the component. By composing a
Modeling Term Structures of Defaultable Bonds
, 1999
"... This article presents convenient reduced-form models of the valuation of contingent claims subject to default risk, focusing on applications to the term structure of interest rates for corporate or sovereign bonds. Examples include the valuation of a credit-spread option ..."
Abstract
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Cited by 672 (34 self)
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This article presents convenient reduced-form models of the valuation of contingent claims subject to default risk, focusing on applications to the term structure of interest rates for corporate or sovereign bonds. Examples include the valuation of a credit-spread option
Nonparametric model for background subtraction
- in ECCV ’00
, 2000
"... Abstract. Background subtraction is a method typically used to seg-ment 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 non-parametric background model and a background subtraction approach. The model can ..."
Abstract
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Cited by 545 (17 self)
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Abstract. Background subtraction is a method typically used to seg-ment 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 non-parametric background model and a background subtraction approach. The model
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353,819
