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64,769
Tractable inference for complex stochastic processes
 In Proc. UAI
, 1998
"... The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system, these tasks typically involve the use of a belief state—a probability distribution over the state of the process at a gi ..."
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Cited by 299 (14 self)
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demonstrate the applicability of our ideas in the context of a monitoring task, showing that orders of magnitude faster inference can be achieved with only a small degradation in accuracy. 1
Tractable Inference Relations
"... We consider the concept of local sets of inference rules. Locality is a syntactic condition on rule sets which guarantees that the inference relation defined by those rules is polynomial time decidable. Unfortunately, determining whether a given rule set is local can be difficult. In this paper we d ..."
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We consider the concept of local sets of inference rules. Locality is a syntactic condition on rule sets which guarantees that the inference relation defined by those rules is polynomial time decidable. Unfortunately, determining whether a given rule set is local can be difficult. In this paper we
Tractable Inference for Probabilistic Data Models
, 2003
"... Based on ideas from statistical physics, we present an approximation technique for probabilistic data models with a large number of hidden variables. We give examples for two non–trivial applications. 1 ..."
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Based on ideas from statistical physics, we present an approximation technique for probabilistic data models with a large number of hidden variables. We give examples for two non–trivial applications. 1
A tractable inference algorithm for diagnosing multiple diseases
 In UAI89
, 1989
"... We examine a probabilistic model for the diagnosis of multiple diseases. In the model, diseases and findings are represented as binary variables. Also, diseases are marginally independent, features are conditionally independent given disease instances, and diseases interact to produce findings via a ..."
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Cited by 56 (0 self)
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We examine a probabilistic model for the diagnosis of multiple diseases. In the model, diseases and findings are represented as binary variables. Also, diseases are marginally independent, features are conditionally independent given disease instances, and diseases interact to produce findings via a noisy orgate. An algorithm for computing the posterior probability of each disease, given a set of observed findings, called quickscore, is presented. The time complexity of the algorithm is O(nm−2m+), where n is the number of diseases, m + is the number of positive findings and m − is the number of negative findings. Although the time complexity of quickscore is exponential in the number of positive findings, the algorithm is useful in practice because the number of observed positive findings is usually far less than the number of diseases under consideration. Performance results for quickscore applied to a probabilistic version of Quick Medical Reference (QMR) are provided. 1
A NonDeterministic Semantics for Tractable Inference
, 1998
"... Unit resolution is arguably the most useful known algorithm for tractable reasoning in propositional logic. Intuitively, if one knows a, b, and a b oe c, then c should be an obvious implication. However, devising a tractable semantics that allows unit resolution has proven to be an elusive goal. W ..."
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Cited by 7 (1 self)
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Unit resolution is arguably the most useful known algorithm for tractable reasoning in propositional logic. Intuitively, if one knows a, b, and a b oe c, then c should be an obvious implication. However, devising a tractable semantics that allows unit resolution has proven to be an elusive goal
Tractable inference systems: an extension with a deducibility predicate
 In CADE’13, LNAI
, 2013
"... Abstract. The main contribution of the paper is a PTIME decision procedure for the satisfiability problem in a class of firstorder Horn clauses. Our result is an extension of the tractable classes of Horn clauses of Basin & Ganzinger in several respects. For instance, our clauses may contain at ..."
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Cited by 8 (7 self)
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Abstract. The main contribution of the paper is a PTIME decision procedure for the satisfiability problem in a class of firstorder Horn clauses. Our result is an extension of the tractable classes of Horn clauses of Basin & Ganzinger in several respects. For instance, our clauses may contain
Reasoning About Set Constraints Applied to Tractable Inference in Intuitionistic Logic
 Journal of Logic and Computation
, 1998
"... Automated reasoning about sets has received a considerable amount of interest in the literature. Techniques for such reasoning have been used in, for instance, analyses of programming languages, terminological logics and spatial reasoning. In this paper, we identify a new class of set constraints wh ..."
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Cited by 6 (2 self)
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where checking satisfiability is tractable (i.e. polynomialtime). We show how to use this tractability result for constructing a new tractable fragment of intuitionistic logic. Furthermore, we prove NPcompleteness of several other cases of reasoning about sets. 1 Introduction There has been
Tractable Inference in Hybrid Bayesian Networks with Deterministic Conditionals using Reapproximations
"... In this paper we study the problem of inference in hybrid Bayesian networks containing deterministic conditionals. The difficulties in handling deterministic conditionals for continuous variables can make inference intractable even for small networks. We describe the use of reapproximations to red ..."
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In this paper we study the problem of inference in hybrid Bayesian networks containing deterministic conditionals. The difficulties in handling deterministic conditionals for continuous variables can make inference intractable even for small networks. We describe the use of re
Generalized Horn Constraints and Tractable Inference on Type Hierarchies with Open Specification
, 2005
"... Large type hierarchies are an integral part of many databases, including in particular lexicons for naturallanguage parsers. Due to their size and complexity, it is often impractical to provide a complete specification. Rather, an open specification is employed, in which properties of the hierarchy ..."
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to the approach is to replace the full logical formulas of general open specification with formulas based upon a special class of disjunctions of Horn sentences. The resulting time complexity, while greater than the linear complexity of propositional Horn inference, is still better than quadratic, and close
Results 1  10
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