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298
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 771 (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
Unsupervised Learning by Probabilistic Latent Semantic Analysis
 Machine Learning
, 2001
"... Abstract. This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter method which stems from linear algebra and performs a Singular Value Decomposition of cooccurren ..."
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Cited by 618 (4 self)
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Abstract. This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter method which stems from linear algebra and performs a Singular Value Decomposition of co
Reasoning about Temporal Relations: A Maximal Tractable Subclass of Allen's Interval Algebra
 Journal of the ACM
, 1995
"... We introduce a new subclass of Allen's interval algebra we call "ORDHorn subclass," which is a strict superset of the "pointisable subclass." We prove that reasoning in the ORDHorn subclass is a polynomialtime problem and show that the pathconsistency method is sufficient ..."
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Cited by 199 (9 self)
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is sufficient for deciding satisfiability. Further, using an extensive machinegenerated case analysis, we show that the ORDHorn subclass is a maximal tractable subclass of the full algebra (assuming<F NaN> P6=NP). In fact, it is the unique greatest tractable subclass amongst the subclasses that contain
Algebraic analysis for nonidentifiable learning machines
 Neural Computation
"... This paper clarifies the relation between the learning curve and the algebraic geometrical structure of a nonidentifiable learning machine such as a multilayer neural network whose true parameter set is an analytic set with singular points. By using a concept in algebraic analysis, we rigorously pr ..."
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Cited by 59 (19 self)
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This paper clarifies the relation between the learning curve and the algebraic geometrical structure of a nonidentifiable learning machine such as a multilayer neural network whose true parameter set is an analytic set with singular points. By using a concept in algebraic analysis, we rigorously
RALL: Machinesupported Proofs for Relation Algebra
 PROCEEDINGS OF CADE14, LECTURE NOTES IN COMPUTER SCIENCE 1249
, 1997
"... We present a theorem proving system for abstract relation algebra called RALL (= RelationAlgebraic Language and Logic), based on the generic theorem prover Isabelle. On the one hand, the system is an advanced case study for Isabelle/HOL, and on the other hand, a quite mature proof assistant for ..."
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Cited by 7 (0 self)
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We present a theorem proving system for abstract relation algebra called RALL (= RelationAlgebraic Language and Logic), based on the generic theorem prover Isabelle. On the one hand, the system is an advanced case study for Isabelle/HOL, and on the other hand, a quite mature proof assistant
Algebraic Geometrical Methods for Hierarchical Learning Machines
, 2001
"... Hierarchical learning machines such as layered perceptrons, radial basis functions, gaussian mixtures are nonidentifiable learning machines, whose Fisher information matrices are not positive definite. This fact shows that conventional statistical asymptotic theory can not be applied to the neural ..."
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Cited by 23 (13 self)
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between the learning curve of a hierarchical learning machine and the algebraic geometrical structure of the parameter space. We establish an algorithm to calculate the Bayesian stochastic complexity based on blowingup technology in algebraic geometry and prove that the Bayesian generalization error of a
Algebraic specification and coalgebraic synthesis of Mealy machines
 In: Proceedings of FACS 2005. ENTCS
, 2006
"... We introduce the notion of functional stream derivative, generalising the notion of input derivative of rational expressions (Brzozowski 1964) to the case of stream functions over arbitrary input and output alphabets. We show how to construct Mealy automata from algebraically specified stream functi ..."
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Cited by 23 (11 self)
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functions by the symbolic computation of functional stream derivatives. We illustrate this construction in full detail for various bitstream functions specified in the algebraic calculus of the 2adic numbers. This work is part of a larger ongoing effort to specify and model component connector circuits
A comparison of empirical and modeldriven optimization
 In ACM Symp. on Programming Language Design and Implementation (PLDI’03
, 2003
"... Empirical program optimizers estimate the values of key optimization parameters by generating different program versions and running them on the actual hardware to determine which values give the best performance. In contrast, conventional compilers use models of programs and machines to choose thes ..."
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Cited by 99 (12 self)
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Empirical program optimizers estimate the values of key optimization parameters by generating different program versions and running them on the actual hardware to determine which values give the best performance. In contrast, conventional compilers use models of programs and machines to choose
Computing with Relational Machines
, 2008
"... Abstract. We give a quick presentation of the Xmachines of Eilenberg, a generalisation of finite state automata suitable for general nondeterministic computation. Such machines complement an automaton, seen as its control component, with a computation component over a data domain specified as an ac ..."
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as an action algebra. Actions are interpreted as binary relations over the data domain, structured by regular expression operations. We show various strategies for the sequential simulation of our relational machines, using variants of the reaction engine. In a particular case of finite machines, we show
Execution Architectures for Program Algebra
, 2004
"... We investigate the notion of an execution architecture in the setting of the program algebra PGA, and distinguish two sorts of these: analytic architectures, designed for the purpose of explanation and provided with a processalgebraic, compositional semantics, and synthetic architectures, focusing ..."
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Cited by 27 (24 self)
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We investigate the notion of an execution architecture in the setting of the program algebra PGA, and distinguish two sorts of these: analytic architectures, designed for the purpose of explanation and provided with a processalgebraic, compositional semantics, and synthetic architectures, focusing
Results 1  10
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298