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GENERALIZED FORMALISM OF MECHANICS By
, 1973
"... The generalized formalism which contains the Lagrangian and Hamiltonian formalisms can be developed in terms of differential geometry [10]. This idea of unification of geometrical and mechanieal theories may be found in the litera ..."
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The generalized formalism which contains the Lagrangian and Hamiltonian formalisms can be developed in terms of differential geometry [10]. This idea of unification of geometrical and mechanieal theories may be found in the litera
Applications Of Circumscription To Formalizing Common Sense Knowledge
 Artificial Intelligence
, 1986
"... We present a new and more symmetric version of the circumscription method of nonmonotonic reasoning first described in (McCarthy 1980) and some applications to formalizing common sense knowledge. The applications in this paper are mostly based on minimizing the abnormality of different aspects o ..."
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Cited by 532 (12 self)
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general formalism called prioritized circumscription is briefly explored. 1 INTRODUCTION ANDNEW DEFINITION OF CIRCUMSCRIPTION (McCarthy 1980) introduces the circumscription method of nonmonotonic reasoning and gives motivation, some mathematical properties and some ex1 amples of its application
Statecharts: A Visual Formalism For Complex Systems
, 1987
"... We present a broad extension of the conventional formalism of state machines and state diagrams, that is relevant to the specification and design of complex discreteevent systems, such as multicomputer realtime systems, communication protocols and digital control units. Our diagrams, which we cal ..."
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Cited by 2704 (56 self)
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alone behavioral description or as part of a more general design methodology that deals also with the system's other aspects, such as functional decomposition and dataflow specification. We also discuss some practical experience that was gained over the last three years in applying the statechart formalism
Improving generalization with active learning
 Machine Learning
, 1994
"... Abstract. Active learning differs from "learning from examples " in that the learning algorithm assumes at least some control over what part of the input domain it receives information about. In some situations, active learning is provably more powerful than learning from examples ..."
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Cited by 544 (1 self)
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alone, giving better generalization for a fixed number of training examples. In this article, we consider the problem of learning a binary concept in the absence of noise. We describe a formalism for active concept learning called selective sampling and show how it may be approximately implemented by a
I: General formalism
, 1996
"... We show how information on the uniformity properties of a point set employed in numerical multidimensional integration can be used to improve the error estimate over the usual Monte Carlo one. We introduce a new measure of (non)uniformity for point sets, and derive explicit expressions for the vari ..."
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We show how information on the uniformity properties of a point set employed in numerical multidimensional integration can be used to improve the error estimate over the usual Monte Carlo one. We introduce a new measure of (non)uniformity for point sets, and derive explicit expressions for the various entities that enter in such an improved error estimate. The use of Feynman diagrams provides a transparent and straightforward way to compute this improved error estimate. Preprint submitted to Computer Physics Communications
General Formalism and Applications.
, 810
"... The Stochastic Vacuum Model for QCD, proposed by Dosch and Simonov, is fused with a Worldline casting of the underlying theory, i.e. QCD. Important, nonperturbative features of the model are studied. In particular, contributions associated with the spinfield interaction are calculated and both the ..."
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The Stochastic Vacuum Model for QCD, proposed by Dosch and Simonov, is fused with a Worldline casting of the underlying theory, i.e. QCD. Important, nonperturbative features of the model are studied. In particular, contributions associated with the spinfield interaction are calculated and both the validity of the loop equations and of the Bianchi identity are explicitly demonstrated. As an application, a simulated mesonmeson scattering problem is studied in the Regge kinematical regime. The process is modeled in terms of the “helicoidal ” Wilson contour along the lines introduced by Janik and Peschanski in a related study based on a AdS/CFTtype approach. Working strictly in the framework of the Stochastic Vacuum Model and in a semiclassical approximation scheme the Regge behavior for the scattering amplitude is demonstrated. Going beyond this approximation, the contribution resulting from boundary fluctuation of the Wilson loop contour is also estimated. PACS: 12.38.t; 12.38.Lg, 12.38.Aw.1. Introduction. The confrontation of nonperturbative issues associated with dynamical processes constitutes
Modeling and simulation of genetic regulatory systems: A literature review
 JOURNAL OF COMPUTATIONAL BIOLOGY
, 2002
"... In order to understand the functioning of organisms on the molecular level, we need to know which genes are expressed, when and where in the organism, and to which extent. The regulation of gene expression is achieved through genetic regulatory systems structured by networks of interactions between ..."
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Cited by 738 (14 self)
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for the modeling and simulation of genetic regulatory networks will be indispensable. This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations
Formal Methods: State of the Art and Future Directions
 ACM Computing Surveys
, 1996
"... ing with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works, requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept, ACM Inc., 1515 Broadway, New York, N ..."
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Cited by 425 (6 self)
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, NY 10036 USA, fax +1 (212) 8690481, or permissions@acm.org. 2 \Delta E.M. Clarke and J.M. Wing About ProgramsMechanical verification, Specification techniques; F.4.1 [Mathematical Logic and Formal Languages]: Mathematical LogicMechanical theorem proving General Terms: Software engineering
Learning in graphical models
 STATISTICAL SCIENCE
, 2004
"... Statistical applications in fields such as bioinformatics, information retrieval, speech processing, image processing and communications often involve largescale models in which thousands or millions of random variables are linked in complex ways. Graphical models provide a general methodology for ..."
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Cited by 806 (10 self)
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for approaching these problems, and indeed many of the models developed by researchers in these applied fields are instances of the general graphical model formalism. We review some of the basic ideas underlying graphical models, including the algorithmic ideas that allow graphical models to be deployed in large
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