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Exploiting WithinClique Factorizations in JunctionTree Algorithms
"... We show that the expected computational complexity of the JunctionTree Algorithm for maximum a posteriori inference in graphical models can be improved. Our results apply whenever the potentials over maximal cliques of the triangulated graph are factored over subcliques. This is common in many rea ..."
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We show that the expected computational complexity of the JunctionTree Algorithm for maximum a posteriori inference in graphical models can be improved. Our results apply whenever the potentials over maximal cliques of the triangulated graph are factored over subcliques. This is common in many
Filtering, Smoothing and the Junction Tree Algorithm
, 1999
"... this paper is the first to show the correspondence explicitely. We use a representation called canonical characteristics [Lau92] instead of the more familiar moment characteristics. The main advantage of this representation is that it allows us to derive a simple twofilter approach to smoothing in ..."
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Cited by 8 (0 self)
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to the standard method of smoothing in LDSs, and which avoids explicitely computing the conditional likelihood (fi) terms. H 1 H 2 \Delta \Delta \Delta HT O 1 O 2 O T 2 The forwardsbackwards algorithm for HMMs
Filtering, Smoothing and the Junction Tree Algorithm
, 1999
"... this paper is the first to show the correspondence explicitely. We use a representation of a Gaussian distribution called canonical characteristics [Lau92], instead of the more familiar moment characteristics, to derive a simple twofilter (ff/ fi) approach to smoothing in LDSs, as is commonly done ..."
Anomaly Based Intrusion Detection Based on the Junction Tree Algorithm
"... Abstract. The aim of this paper is to present a methodology for the attacks recognition during the normal activities in the system. Since the proposed approach uses the graphical representation method, we apply the junction tree algorithm (JTA). Some results from the accomplished simulation experime ..."
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Cited by 2 (0 self)
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Abstract. The aim of this paper is to present a methodology for the attacks recognition during the normal activities in the system. Since the proposed approach uses the graphical representation method, we apply the junction tree algorithm (JTA). Some results from the accomplished simulation
Variational Approximations between Mean Field Theory and the Junction Tree Algorithm
 In Uncertainty in Artificial Intelligence
, 2000
"... Recently, variational approximations such as the mean field approximation have received much interest. We extend the standard mean field method by using an approximating distribution that factorises into cluster potentials. This includes undirected graphs, directed acyclic graphs and junction ..."
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Cited by 51 (1 self)
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trees. We derive generalised mean field equations to optimise the cluster potentials. We show that the method bridges the gap between the standard mean field approximation and the exact junction tree algorithm. In addition, we address the problem of how to choose the structure and the free
The InclusionExclusion Rule and its Application to the Junction Tree Algorithm
, 2013
"... In this paper, we consider the inclusionexclusion rule – a known yet seldom used rule of probabilistic inference. Unlike the widely used sum rule which requires easy access to all joint probability values, the inclusionexclusion rule requires easy access to several marginal probability values. We ..."
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Cited by 1 (0 self)
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scheme was an order of magnitude faster than the junction tree algorithm.
Some Evaluations of the Effectiveness of Anomaly Based Intrusion Detection Systems Based on the Junction Tree Algorithm
"... ABSTRACT The aim of this paper is to present some evaluations of the effectiveness of IDS based on the junction tree algorithm (JTA). We stop our attention to two statistical methods sensitivity and specificity which are functions of the true positive rate, the false negative rate and the false po ..."
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ABSTRACT The aim of this paper is to present some evaluations of the effectiveness of IDS based on the junction tree algorithm (JTA). We stop our attention to two statistical methods sensitivity and specificity which are functions of the true positive rate, the false negative rate and the false
Dynamic Bayesian Networks: Representation, Inference and Learning
, 2002
"... Modelling sequential data is important in many areas of science and engineering. Hidden Markov models (HMMs) and Kalman filter models (KFMs) are popular for this because they are simple and flexible. For example, HMMs have been used for speech recognition and biosequence analysis, and KFMs have bee ..."
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Cited by 770 (3 self)
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) space instead of O(T); a simple way of using the junction tree algorithm for online inference in DBNs; new complexity bounds on exact online inference in DBNs; a new deterministic approximate inference algorithm called factored frontier; an analysis of the relationship between the BK algorithm and loopy
Induction of Decision Trees
 MACH. LEARN
, 1986
"... The technology for building knowledgebased systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such syste ..."
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Cited by 4377 (4 self)
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The technology for building knowledgebased systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one
Constructing Free Energy Approximations and Generalized Belief Propagation Algorithms
 IEEE Transactions on Information Theory
, 2005
"... Important inference problems in statistical physics, computer vision, errorcorrecting coding theory, and artificial intelligence can all be reformulated as the computation of marginal probabilities on factor graphs. The belief propagation (BP) algorithm is an efficient way to solve these problems t ..."
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Cited by 585 (13 self)
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to generate valid approximations: the “Bethe method, ” the “junction graph method, ” the “cluster variation method, ” and the “region graph method.” Finally, we explain how to tell whether a regionbased approximation, and its corresponding GBP algorithm, is likely to be accurate, and describe empirical
Results 1  10
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