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Consistency Theorems for Discrete Bayesian Learning
"... Bayes ’ rule specifies how to obtain a posterior from a class of hypotheses endowed with a prior and the observed data. There are three fundamental ways to use this posterior for predicting the future: marginalization (integration over the hypotheses w.r.t. the posterior), MAP (taking the a posterio ..."
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posteriori most probable hypothesis), and stochastic model selection (selecting a hypothesis at random according to the posterior distribution). If the hypothesis class is countable and contains the data generating distribution (this is termed the “realizable case”), strong consistency theorems are known
An Extended Joint Consistency Theorem for a Nonconstructive Logic Of . . .
, 2002
"... The logic of partial terms (LPT) is a variety of negative free logic in which functions, as well as predicates, are strict. A companion paper focused on nonconstructive LPT with de nite descriptions, called LPD, and laid the foundation for tableaux systems by de ning the concept of an LPD model s ..."
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Cited by 2 (0 self)
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system and establishing Hintikka's Lemma, from which the strong completeness of the corresponding tableaux system readily follows. The present paper utilizes the tableaux system in establishing an Extended Joint Consistency Theorem for LPD that incorporates the Robinson Joint Consistency Theorem
Model Checking Programs
, 2003
"... The majority of work carried out in the formal methods community throughout the last three decades has (for good reasons) been devoted to special languages designed to make it easier to experiment with mechanized formal methods such as theorem provers, proof checkers and model checkers. In this pape ..."
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Cited by 592 (63 self)
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The majority of work carried out in the formal methods community throughout the last three decades has (for good reasons) been devoted to special languages designed to make it easier to experiment with mechanized formal methods such as theorem provers, proof checkers and model checkers
GSAT and Dynamic Backtracking
 Journal of Artificial Intelligence Research
, 1994
"... There has been substantial recent interest in two new families of search techniques. One family consists of nonsystematic methods such as gsat; the other contains systematic approaches that use a polynomial amount of justification information to prune the search space. This paper introduces a new te ..."
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Cited by 386 (15 self)
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There has been substantial recent interest in two new families of search techniques. One family consists of nonsystematic methods such as gsat; the other contains systematic approaches that use a polynomial amount of justification information to prune the search space. This paper introduces a new
An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation
 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
, 1993
"... A novel graph theoretic approach for data clustering is presented and its application to the image segmentation problem is demonstrated. The data to be clustered are represented by an undirected adjacency graph G with arc capacities assigned to reflect the similarity between the linked vertices. Cl ..."
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Cited by 360 (0 self)
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constructed using the GomoryHu algorithm. However for larger graphs this approach is impractical. New theorems for subgraph condensation are derived and are then used to develop a fast algorithm which hierarchically constructs and partitions a partially equivalent tree of much reduced size. This algorithm
A CounterExample to Tomek's Consistency Theorem for a Condensed Nearest Neighbor Decision Rule
 Rule, Pattern Recognition Letters
, 1994
"... The condensed nearest neighbor rule (CNN) was proposed by Hart [Ha68] as a method to reduce the storage requirements of the original data set D for the efficient implementation of the nearest neighbor decision rule in pattern classification problems. Tomek [To76a] suggested two modifications of CNN ..."
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Cited by 4 (1 self)
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in order to improve its performance. As a first step in Tomek's second method he computes a subset C of D, for subsequent use in CNN, and claims that C is trainingsetconsistent, i.e., that all data points in D are correctly classified by the nearest neighbor rule using C. In this note we provide a
Language primitives and type discipline for structured communicationbased programming
 In ESOP’98, volume 1381 of LNCS
, 1998
"... Session primitives and types provide a flexible programming style for structured interaction, and are used to statically check the safe and consistent composition of protocols in communicationcentric distributed software. Unfortunately authors working on session types have recently realised that so ..."
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Cited by 309 (64 self)
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Session primitives and types provide a flexible programming style for structured interaction, and are used to statically check the safe and consistent composition of protocols in communicationcentric distributed software. Unfortunately authors working on session types have recently realised
Splitting a Logic Program
 Principles of Knowledge Representation
, 1994
"... In many cases, a logic program can be divided into two parts, so that one of them, the \bottom " part, does not refer to the predicates de ned in the \top " part. The \bottom " rules can be used then for the evaluation of the predicates that they de ne, and the computed va ..."
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Cited by 294 (16 self)
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values can be used to simplify the \top " de nitions. We discuss this idea of splitting a program in the context of the answer set semantics. The main theorem shows how computing the answer sets for a program can be simpli ed when the program is split into parts. The programs covered
Generalized Arc Consistency for Global Cardinality Constraint
"... A global cardinality constraint (gcc) is specified in terms of a set of variables X = fx1 ; :::; xpg which take their values in a subset of V = fv1 ; :::; vdg. It constrains the number of times a value v i 2 V is assigned toavariable in X to be in an interval (l i ;c i ). Cardinality constraints hav ..."
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Cited by 204 (11 self)
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have proved very useful in many reallife problems, suchas scheduling, timetabling, or resource allocation. A gcc is more general than a constraint of difference, which requires each interval to be #0; 1#. In this paper, we present an efficient way of implementing generalized arc consistency for a gcc
Maximum score estimation of the stochastic utility model of choice
 Journal of Econometrics
, 1975
"... This paper introduces a class of robust estimators of the parameters of a stochastic utility function. Existing maximum likelihood and regression estimation methods require the assumption of a particular distributional family for the random component of utility. In contrast, estimators of the ‘maxi ..."
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Cited by 204 (2 self)
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of the ‘maximum score ’ class require only weak distributional assumptions for consistency. Following presentation and proof of the basic consistency theorem, additional results are given. An algorithm for achieving maximum score estimates and some small sample Monte Carlo tests are also described. 1.
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