Inference in probabilistic graphical models (PGMs) does typically not allow for analytical solutions, confining us to various approximative methods. We propose a sequential Monte Carlo (SMC) algorithm for inference in general PGMs. Via a sequential decomposition of the PGM we find a sequence of auxiliary distributions defined on a monotonically increasing sequence of probability spaces. By targ...

We present provably correct interactive algorithms for learning regular grammars from positive examples and membership queries. A structurally complete set of strings from a language L(G) corresponding to a target regular grammar G implicitly speciies a lattice of nite state automata (FSA) which contains a FSA MG corresponding to G. The lattice is compactly represented as a version-space and MG...

This paper discusses the relationship between the property of paraconsistency and Statistical Default Logic, a nonmonotonic logic that models common inference forms found in classical statistical inference such as hypothesis testing and the estimation of a population’s mean, variance and proportions. Statistical Default Logic is paraconsistent in the sense that a set of default inference forms ...

This paper designs methods of product differences testing and preference testing by using triangle taste tests data. Binomial distribution theory and hypothesis test method are employed since that the existing statistical inference methods of triangle taste tests methods for sensory and quality analysis of cigarette products have some shortcomings. Finally, two case studies are provided, which ...

Recently, an algorithm DEESwas proposed for learning rational stochastic tree languages. Given a sample of trees independently and identically drawn according to a distribution de ned by a rational stochastic language, DEES outputs a linear representation of a rational series which converges to the target. DEES can then be used to identify in the limit with probability one rational stochastic t...

In this paper, an α-resolution method for a set of lattice-valued Horn generalized clauses is established in lattice-valued propositional logic systemL P(X) based on lattice implication algebra. Firstly, the notions of lattice-valued Horn generalized clause, normal lattice-valued Horn generalized clause and unit latticevalued Horn generalized clause are given in L P(X). Then, the α-resolution o...

Medical image fusion is one of the popular research topics. Medical image fusion generally means the matching and fusion between two or more images of the same lesion area from different medical imaging equipment. Medical image fusion aims to obtain complementary information and also increase the amount of information. Medical image fusion technique is to combine the information of a variety of...

Modern Chaff-like SAT solvers enhance plain backtracking (DLL) by Conflict-Driven Learning (CDL), including 1UIP-based Conflict-Directed Backjumping (CDB), Non-Chronological Backtracking (NCB), and 1UIP-based Conflict-Clause Recording (CCR). We show how to add these enhancements step-by-step to plain DLL to derive Chaff’s Conflict-Driven Learning algorithm, separately and independently of BCP, ...

The paper proposes a key constraint language for XML and investigates its associated decision problems. The language is deened in terms of regular path expressions extended with downward and upward wildcards, which can not only move down XML document trees, but also upwards as well. In a uniform syntax it is capable of expressing both absolute keys and relative keys, which are important for hie...

In order to make overall consideration of the information from the original variables in the basic oxygen furnace (BOF) steelmaking dynamic process, an adaptive neural network fuzzy inference system (ANFIS) model based on kernel and greedy components is proposed. This kind of model can improve the endpoint predicting precision of the steel carbon contents and temperature. After hidden informati...