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# IEEE Transactions on Pattern Analysis and Machine Intelligence

## Filter Results

Displaying Results 1 - 13 of 13
• ### On an asymptotically optimal adaptive classifier design criterion

Publication Year: 1993, Page(s):312 - 318
Cited by:  Papers (1)
| | PDF (616 KB)

A new approach for estimating classification errors is presented. In the model, there are two types of classification error: empirical and generalization error. The first is the error observed over the training samples, and the second is the discrepancy between the error probability and empirical error. In this research, the Vapnik and Chervonenkis dimension (VCdim) is used as a measure for classi... View full abstract»

• ### Local reproducible smoothing without shrinkage

Publication Year: 1993, Page(s):307 - 312
Cited by:  Papers (28)  |  Patents (3)
| | PDF (516 KB)

A simple local smoothing filter is defined for curves or surfaces, combining the advantages of Gaussian smoothing and Fourier curve description. Unlike Gaussian filters, the filter described has no shrinkage problem. Repeated application of the filter does not yield a curve or surface smaller than the original but simply reproduces the approximate result that would have been obtained by a single a... View full abstract»

• ### Dynamic network construction and updating techniques for the diagnosis of acute abdominal pain

Publication Year: 1993, Page(s):299 - 307
Cited by:  Papers (28)
| | PDF (920 KB)

Computing diagnoses in domains with continuously changing data is difficult but essential aspect of solving many problems. To address this task, a dynamic influence diagram (ID) construction and updating system (DYNASTY) and its application to constructing a decision-theoretic model to diagnose acute abdominal pain, which is a domain in which the findings evolve during the diagnostic process, are ... View full abstract»

• ### An approximate nonmyopic computation for value of information

Publication Year: 1993, Page(s):292 - 298
Cited by:  Papers (28)  |  Patents (1)
| | PDF (604 KB)

It is argued that decision analysts and expert-system designers have avoided the intractability of exact computation of the value of information by relying on a myopic assumption that only one additional test will be performed, even when there is an opportunity to make large number of observations. An alternative to the myopic analysis is presented. In particular, an approximate method for computi... View full abstract»

• ### Explaining explaining away'

Publication Year: 1993, Page(s):287 - 292
Cited by:  Papers (28)
| | PDF (604 KB)

Explaining away' is a common pattern of reasoning in which the confirmation of one cause of an observed or believed event reduces the need to invoke alternative causes. The opposite of explaining away also an occur, where the confirmation of one cause increases belief in another. A general qualitative probabilistic analysis of intercausal reasoning is provided and the property of the interaction ... View full abstract»

• ### Structural and probabilistic knowledge for abductive reasoning

Publication Year: 1993, Page(s):233 - 245
Cited by:  Papers (6)  |  Patents (2)
| | PDF (1224 KB)

Different ways of representing probabilistic relationships among the attributes of a domain ar examined, and it is shown that the nature of domain relationships used in a representation affects the types of reasoning objectives that can be achieved. Two well-known formalisms for representing the probabilistic among attributes of a domain. These are the dependence tree formalism presented by C.K. C... View full abstract»

• ### Integration, inference, and management of spatial information using Bayesian networks: perceptual organization

Publication Year: 1993, Page(s):256 - 274
Cited by:  Papers (84)  |  Patents (3)
| | PDF (1544 KB)

The formalism of Bayesian networks provides a very elegant solution, in a probabilistic framework, to the problem of integrating top-down and bottom-up visual processes, as well serving as a knowledge base. The formalism is modified to handle spatial data, and thus the application of Bayesian networks is extended to visual processing. The modified form is called the perceptual inference network (P... View full abstract»

• ### Probability intervals over influence diagrams

Publication Year: 1993, Page(s):280 - 286
Cited by:  Papers (8)
| | PDF (580 KB)

A mechanism for performing probabilistic reasoning in influence diagrams using interval rather than point-valued probabilities is described. Procedures for operations corresponding to conditional expectation and Bayesian conditioning in influence diagrams are derived where lower bounds on probabilities are stored at each node. The resulting bounds for the transformed diagram are shown to be the ti... View full abstract»

• ### A maximum entropy approach to nonmonotonic reasoning

Publication Year: 1993, Page(s):220 - 232
Cited by:  Papers (33)
| | PDF (1224 KB)

An approach to nonmonotonic reasoning that combines the principle of infinitesimal probabilities with that of maximum entropy, thus extending the inferential power of the probabilistic interpretation of defaults, is proposed. A precise formalization of the consequences entailed by a conditional knowledge base is provided, the computational machinery necessary for drawing these consequences is deve... View full abstract»

• ### Approximating probabilistic inference in Bayesian belief networks

Publication Year: 1993, Page(s):246 - 255
Cited by:  Papers (29)  |  Patents (3)
| | PDF (864 KB)

A belief network comprises a graphical representation of dependencies between variables of a domain and a set of conditional probabilities associated with each dependency. Unless ρ=NP, an efficient, exact algorithm does not exist to compute probabilistic inference in belief networks. Stochastic simulation methods, which often improve run times, provide an alternative to exact inference algorit... View full abstract»

• ### Causal probabilistic networks with both discrete and continuous variables

Publication Year: 1993, Page(s):275 - 279
Cited by:  Papers (13)  |  Patents (2)
| | PDF (468 KB)

An extension of the expert system shell known as handling uncertainty by general influence networks (HUGIN) to include continuous variables, in the form of linear additive normally distributed variables, is presented. The theoretical foundation of the method was developed by S.L. Lauritzen, whereas this report primarily focus on implementation aspects. The approach has several advantages over pure... View full abstract»

• ### A language for construction of belief networks

Publication Year: 1993, Page(s):196 - 208
Cited by:  Papers (19)  |  Patents (5)
| | PDF (1232 KB)

A method for incrementally constructing belief networks, which are directed acyclic graph representations for probability distributions, is described. A network-construction language, FRAIL3, which is similar to a forward-chaining language using data dependencies but has additional features for specifying distributions, was developed. A particularly important feature of this language is that is al... View full abstract»

• ### Sequential model criticism in probabilistic expert systems

Publication Year: 1993, Page(s):209 - 219
Cited by:  Papers (19)  |  Patents (4)
| | PDF (904 KB)

Probabilistic expert systems based on Bayesian networks require initial specification of both qualitative graphical structure and quantitative conditional probability assessments. As (possibly incomplete) data accumulate on real cases, the parameters of the system may adapt, but it is also essential that the initial specifications be monitored with respect to their predictive performance. A range ... View full abstract»

## Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Sven Dickinson
University of Toronto
e-mail: sven@cs.toronto.edu