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Abstract interpretation of probabilistic semantics
 In Seventh International Static Analysis Symposium (SAS’00), number 1824 in Lecture Notes in Computer Science
, 2000
"... Abstract. Following earlier models, we lift standard deterministic and nondeterministic semantics of imperative programs to probabilistic semantics. This semantics allows for random external inputs of known or unknown probability and random number generators. We then propose a method of analysis of ..."
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Cited by 38 (5 self)
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Abstract. Following earlier models, we lift standard deterministic and nondeterministic semantics of imperative programs to probabilistic semantics. This semantics allows for random external inputs of known or unknown probability and random number generators. We then propose a method of analysis
Probabilistic semantics for cost based abduction
 In Proceedings of AAAI90
, 1990
"... Costbased abduction attempts to find the best explanation for a set of facts by finding a minimal cost proof for the facts. The costs are computed by summing the costs of the assumptions necessary for the proof plus the cost of the rules. We examine existing methods for constructing explanations (p ..."
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Cited by 47 (1 self)
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(proofs), as a minimization problem on a DAG. We then define a probabilistic semantics for the costs, and prove the equivalence of the cost minimization problem to the Bayesian network MAP solution of the system.
Probabilistic Semantic Video Indexing
 In Proceedings of Neural Information Processing Systems
, 2000
"... We propose a novel probabilistic framework for semantic video indexing. ..."
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Cited by 7 (2 self)
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We propose a novel probabilistic framework for semantic video indexing.
Probabilistic Semantically Reliable Multicast
"... Traditional broadcast protocols fail to scale to large settings. Several recent attempts have proven efficient to ensure reliable information dissemination in groups composed of a large number of participants. This paper proposes a reliable multicast protocol that integrates two complementary app ..."
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Cited by 7 (4 self)
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approaches to deal with the largescale dimension in group communication protocols: gossipbased probabilistic and semanticbased protocols. Although it seems
Probabilistic Latent Semantic Indexing
, 1999
"... Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized ..."
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Cited by 1207 (11 self)
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Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized
Probabilistic Latent Semantic Analysis
 In Proc. of Uncertainty in Artificial Intelligence, UAI’99
, 1999
"... Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of twomode and cooccurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent Sema ..."
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Cited by 760 (9 self)
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Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of twomode and cooccurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent
Probabilistic Semantic Analysis of Speech
 Mustererkennung 1997, DAGM Symposium
, 1997
"... . This paper presents a new probabilistic approach to semantic analysis of speech. The problem of finding the semantic contents of a word chain is modeled as the problem of assigning semantic attributes to words. The discrete assignment function is characterized by random vectors and its probabiliti ..."
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Cited by 2 (2 self)
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. This paper presents a new probabilistic approach to semantic analysis of speech. The problem of finding the semantic contents of a word chain is modeled as the problem of assigning semantic attributes to words. The discrete assignment function is characterized by random vectors and its
Probabilistic Semantics and Program Analysis
"... Abstract. The aims of these lecture notes are twofold: (i) we investigate the relation between the operational semantics of probabilistic programming languages and Discrete Time Markov Chains (DTMCs), and (ii) we present a framework for probabilistic program analysis which is inspired by the classi ..."
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Cited by 1 (0 self)
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Abstract. The aims of these lecture notes are twofold: (i) we investigate the relation between the operational semantics of probabilistic programming languages and Discrete Time Markov Chains (DTMCs), and (ii) we present a framework for probabilistic program analysis which is inspired
The Weakest Completion Approach to the Probabilistic Semantics
, 2000
"... A standard program starts its execution in an initial state, and terminates (if it ever does) in one of a set of final states. Its behaviour can be modelled by a binary relation between the initial and final states. The difference between the standard and the probabilistic semantics is that the form ..."
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Cited by 1 (0 self)
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A standard program starts its execution in an initial state, and terminates (if it ever does) in one of a set of final states. Its behaviour can be modelled by a binary relation between the initial and final states. The difference between the standard and the probabilistic semantics
A Probabilistic Semantics for Timed Automata
"... Like most models used in modelchecking, timed automata are an ideal mathematical model to represent systems with strong timing requirements. In such mathematical models, properties can be violated, due to unlikely events. Following ideas of Varacca and Völzer [VV06], we aim at defining a notion o ..."
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of “fair” correctness for timed systems. For this purpose, we introduce a probabilistic semantics for timed automata, which ignores unlikely events, and naturally raises a notion of almostsure satisfaction of properties in timed systems. We prove that the almostsure satisfaction has a corresponding
Results 1  10
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82,738