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20,538
Long memory relationships and the aggregation of dynamic models
 Journal of Econometrics
, 1980
"... By aggregating simple. possibly dependent, dynamic microrelationships, it is shown that the aggregate series may have univariate longmemory models and obey integrated, or infinite length transfer function relationships. A longmemory time series model is one having spectrum or order 6 ” for small ..."
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Cited by 358 (3 self)
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By aggregating simple. possibly dependent, dynamic microrelationships, it is shown that the aggregate series may have univariate longmemory models and obey integrated, or infinite length transfer function relationships. A longmemory time series model is one having spectrum or order 6 ” for small frequencies w, d>O. These models have infinite variance for d If but finite variance for dc+. For d = 1 the series that need to be differenced to achieve stationarity occur, but this case is not found to occur from aggregation. It is suggested that if series obeying such models occur in practice, from aggregation, then present techniques being used for analysis are not appropriate. 1.
Global Economic Prospects and the Developing Countries 2000. Washington,D.C
, 1999
"... The findings, interpretations, and conclusions expressed here do not necessarily reflect the views of the Board of Executive Directors of the World Bank or the governments they represent. The World Bank cannot guarantee the accuracy of the data included in this work. The boundaries, colors, denomina ..."
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Cited by 358 (3 self)
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The findings, interpretations, and conclusions expressed here do not necessarily reflect the views of the Board of Executive Directors of the World Bank or the governments they represent. The World Bank cannot guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply on the part of the World Bank any judgment of the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this work is copyrighted. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or inclusion in any information storage and retrieval system, without the prior
Gravity coupled with matter and the foundation of non commutative geometry
, 1996
"... We first exhibit in the commutative case the simple algebraic relations between the algebra of functions on a manifold and its infinitesimal length element ds. Its unitary representations correspond to Riemannian metrics and Spin structure while ds is the Dirac propagator ds = ×— × = D −1 where D i ..."
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Cited by 354 (18 self)
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We first exhibit in the commutative case the simple algebraic relations between the algebra of functions on a manifold and its infinitesimal length element ds. Its unitary representations correspond to Riemannian metrics and Spin structure while ds is the Dirac propagator ds = ×— × = D −1 where D is the Dirac operator. We extend these simple relations to the non commutative case using Tomita’s involution J. We then write a spectral action, the trace of a function of the length element in Planck units, which when applied to the non commutative geometry of the Standard Model will be shown (in a joint work with Ali Chamseddine) to give the SM Lagrangian coupled to gravity. The internal fluctuations of the non commutative geometry are trivial in the commutative case but yield the full bosonic sector of SM with all correct quantum numbers in the slightly non commutative case. The group of local gauge transformations appears spontaneously as a normal subgroup of the diffeomorphism group.
Intrusion Detection via Static Analysis
, 2001
"... One of the primary challenges in intrusion detection is modelling typical application behavior, so that we can recognize attacks by their atypical effects without raising too many false alarms. We show how static analysis may be used to automatically derive a model of application behavior. The resul ..."
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Cited by 349 (1 self)
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One of the primary challenges in intrusion detection is modelling typical application behavior, so that we can recognize attacks by their atypical effects without raising too many false alarms. We show how static analysis may be used to automatically derive a model of application behavior. The result is a hostbased intrusion detection system with three advantages: a high degree of automation, protection against a broad class of attacks based on corrupted code, and the elimination of false alarms. We report on our experience with a prototype implementation of this technique. 1. Introduction Computer security has undergone a major renaissance in the last five years. Beginning with Sun's introduction of the Java language and its support of mobile code in 1995, programming languages have been a major focus of security research. Many papers have been published applying programming language theory to protection problems [25, 24], especially information flow [17]. Security, however, is a ma...
Cryptographic Limitations on Learning Boolean Formulae and Finite Automata
 PROCEEDINGS OF THE TWENTYFIRST ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING
, 1989
"... In this paper we prove the intractability of learning several classes of Boolean functions in the distributionfree model (also called the Probably Approximately Correct or PAC model) of learning from examples. These results are representation independent, in that they hold regardless of the syntact ..."
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Cited by 347 (15 self)
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In this paper we prove the intractability of learning several classes of Boolean functions in the distributionfree model (also called the Probably Approximately Correct or PAC model) of learning from examples. These results are representation independent, in that they hold regardless of the syntactic form in which the learner chooses to represent its hypotheses. Our methods reduce the problems of cracking a number of wellknown publickey cryptosystems to the learning problems. We prove that a polynomialtime learning algorithm for Boolean formulae, deterministic finite automata or constantdepth threshold circuits would have dramatic consequences for cryptography and number theory: in particular, such an algorithm could be used to break the RSA cryptosystem, factor Blum integers (composite numbers equivalent to 3 modulo 4), and detect quadratic residues. The results hold even if the learning algorithm is only required to obtain a slight advantage in prediction over random guessing. The techniques used demonstrate an interesting duality between learning and cryptography. We also apply our results to obtain strong intractability results for approximating a generalization of graph coloring.
Differential Fault Analysis of Secret Key Cryptosystems
, 1997
"... In September 1996 Boneh, Demillo, and Lipton from Bellcore announced a new type of cryptanalytic attack which exploits computational errors to find cryptographic keys. Their attack is based on algebraic properties of modular arithmetic, and thus it is applicable only to public key cryptosystems suc ..."
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Cited by 310 (3 self)
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such as RSA, and not to secret key algorithms such as the Data Encryption Standard (DES). In this paper, we describe a related attack, which we call Differential Fault Analysis, or DFA, and show that it is applicable to almost any secret key cryptosystem proposed so far in the open literature. Our DFA attack
Automated Grading of DFA Constructions ∗
"... One challenge in making online education more effective is to develop automatic grading software that can provide meaningful feedback. This paper provides a solution to automatic grading of the standard computationtheory problem that asks a student to construct a deterministic finite automaton (DFA ..."
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Cited by 7 (3 self)
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(DFA) from the given description of its language. We focus on how to assign partial grades for incorrect answers. Each student’s answer is compared to the correct DFA using a hybrid of three techniques devised to capture different classes of errors. First, in an attempt to catch syntactic mistakes, we
DFA learning of opponent strategies
 In Proceedings of the Florida AI Research Symposium
, 1998
"... This work studies the control of robots in the adversarial world of “Hunt the Wumpus”. The hybrid learning algorithm which controls the robots behavior is a combination of a modified RPNI algorithm, and a utility update algorithm. The modified RPNI algorithm is a DFA learning algorithm, to learn opp ..."
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Cited by 3 (0 self)
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This work studies the control of robots in the adversarial world of “Hunt the Wumpus”. The hybrid learning algorithm which controls the robots behavior is a combination of a modified RPNI algorithm, and a utility update algorithm. The modified RPNI algorithm is a DFA learning algorithm, to learn
Synchronization of some DFA
 Lect. Notes in Comp. Sci, Springer,4484(2007), TAMC 2007
"... Abstract. A word w is called synchronizing (recurrent, reset, directable) word of deterministic finite automaton (DFA) if w brings all states of the automaton to an unique state. Černy conjectured in 1964 that every nstate synchronizable automaton possesses a synchronizing word of length at most (n ..."
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Cited by 1 (1 self)
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Abstract. A word w is called synchronizing (recurrent, reset, directable) word of deterministic finite automaton (DFA) if w brings all states of the automaton to an unique state. Černy conjectured in 1964 that every nstate synchronizable automaton possesses a synchronizing word of length at most
Correlation And Dependence In Risk Management: Properties And Pitfalls
 RISK MANAGEMENT: VALUE AT RISK AND BEYOND
, 1999
"... Modern risk management calls for an understanding of stochastic dependence going beyond simple linear correlation. This paper deals with the static (nontimedependent) case and emphasizes the copula representation of dependence for a random vector. Linear correlation is a natural dependence measure ..."
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Cited by 319 (37 self)
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Modern risk management calls for an understanding of stochastic dependence going beyond simple linear correlation. This paper deals with the static (nontimedependent) case and emphasizes the copula representation of dependence for a random vector. Linear correlation is a natural dependence measure for multivariate normally and, more generally, elliptically distributed risks but other dependence concepts like comonotonicity and rank correlation should also be understood by the risk management practitioner. Using counterexamples the falsity of some commonly held views on correlation is demonstrated; in general, these fallacies arise from the naive assumption that dependence properties of the elliptical world also hold in the nonelliptical world. In particular, the problem of finding multivariate models which are consistent with prespecified marginal distributions and correlations is addressed. Pitfalls are highlighted and simulation algorithms avoiding these problems are constructed. ...
Results 11  20
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