20,904 research outputs found
Multivariate integration of functions depending explicitly on the minimum and the maximum of the variables
By using some basic calculus of multiple integration, we provide an
alternative expression of the integral in which the minimum and the maximum are replaced
with two single variables. We demonstrate the usefulness of that expression in
the computation of orness and andness average values of certain aggregation
functions. By generalizing our result to Riemann-Stieltjes integrals, we also
provide a method for the calculation of certain expected values and
distribution functions.Comment: 15 page
Oblivious Bounds on the Probability of Boolean Functions
This paper develops upper and lower bounds for the probability of Boolean
functions by treating multiple occurrences of variables as independent and
assigning them new individual probabilities. We call this approach dissociation
and give an exact characterization of optimal oblivious bounds, i.e. when the
new probabilities are chosen independent of the probabilities of all other
variables. Our motivation comes from the weighted model counting problem (or,
equivalently, the problem of computing the probability of a Boolean function),
which is #P-hard in general. By performing several dissociations, one can
transform a Boolean formula whose probability is difficult to compute, into one
whose probability is easy to compute, and which is guaranteed to provide an
upper or lower bound on the probability of the original formula by choosing
appropriate probabilities for the dissociated variables. Our new bounds shed
light on the connection between previous relaxation-based and model-based
approximations and unify them as concrete choices in a larger design space. We
also show how our theory allows a standard relational database management
system (DBMS) to both upper and lower bound hard probabilistic queries in
guaranteed polynomial time.Comment: 34 pages, 14 figures, supersedes: http://arxiv.org/abs/1105.281
On the succinctness of query rewriting over shallow ontologies
We investigate the succinctness problem for conjunctive query rewritings over OWL2QL ontologies of depth 1 and 2 by means of hypergraph programs computing Boolean functions. Both positive and negative results are obtained. We show that, over ontologies of depth 1, conjunctive queries have polynomial-size nonrecursive datalog rewritings; tree-shaped queries have polynomial positive existential rewritings; however, in the worst case, positive existential rewritings can be superpolynomial. Over ontologies of depth 2, positive existential and nonrecursive datalog rewritings of conjunctive queries can suffer an exponential blowup, while first-order rewritings can be superpolynomial unless NP �is included in P/poly. We also analyse rewritings of tree-shaped queries over arbitrary ontologies and note that query entailment for such queries is fixed-parameter tractable
Ranking Templates for Linear Loops
We present a new method for the constraint-based synthesis of termination
arguments for linear loop programs based on linear ranking templates. Linear
ranking templates are parametrized, well-founded relations such that an
assignment to the parameters gives rise to a ranking function. This approach
generalizes existing methods and enables us to use templates for many different
ranking functions with affine-linear components. We discuss templates for
multiphase, piecewise, and lexicographic ranking functions. Because these
ranking templates require both strict and non-strict inequalities, we use
Motzkin's Transposition Theorem instead of Farkas Lemma to transform the
generated -constraint into an -constraint.Comment: TACAS 201
Closed classes of functions, generalized constraints and clusters
Classes of functions of several variables on arbitrary non-empty domains that
are closed under permutation of variables and addition of dummy variables are
characterized in terms of generalized constraints, and hereby Hellerstein's
Galois theory of functions and generalized constraints is extended to infinite
domains. Furthermore, classes of operations on arbitrary non-empty domains that
are closed under permutation of variables, addition of dummy variables and
composition are characterized in terms of clusters, and a Galois connection is
established between operations and clusters.Comment: 21 page
The Dichotomy of Conjunctive Queries on Probabilistic Structures
We show that for every conjunctive query, the complexity of evaluating it on
a probabilistic database is either \PTIME or #\P-complete, and we give an
algorithm for deciding whether a given conjunctive query is \PTIME or
#\P-complete. The dichotomy property is a fundamental result on query
evaluation on probabilistic databases and it gives a complete classification of
the complexity of conjunctive queries
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