10922325
Quantified Constraint Satisfaction and Bounded Treewidth
Because the constraint satisfaction problem (CSP) is in general intractable, restricted cases of the CSP that are polynomial-time tractable have been heavily sought after. One class of restrictions that has been studied are variable-based restrictions, which concern the interaction among variables. In this paper, we consider the quantified constraint satisfaction problem (QCSP), a framework more general than the CSP. We present a QCSP tractability result arising from variable-based restrictions by giving a polynomial time algorithm for certain classes of QCSP instances having bounded treewidth.
9351295
Looking Algebraically at Tractable Quantified Boolean Formulas
We make use of the algebraic theory that has been used to study the complexity of constraint satisfaction problems, to investigate tractable quantified boolean formulas. We present a pair of results: the first is a new and simple algebraic proof of the tractability of quantified 2-satisfiability; the second is a purely algebraic characterization of models for quantified Horn formulas that were given by Kleine Buning, Subramani, and Zhao, and described proof-theoretically.
958592
Inverse Circumscription
Inverse (or identification) problems involve deciding whether or not an explicitly given set of data points have an implicit description, for instance, in the form of a constraint network. Such problems provide insight into the relationships among various representations of knowledge, which may have differing computational properties. This paper formalizes and studies the inverse circumscription problem, which (roughly speaking) is to decide, given a set of models, if there exists a formula whose circumscription describes the input set.
3121075
Parameterized Compilability
Compilability is a measure of how effectively compilation (or preprocessing) can be applied to knowledge bases specified in a particular knowledge representation formalism; the aim of compilation is to allow for efficient, on-line query processing. A theory of compilability has been established for organizing knowledge representation formalisms according to a scheme of "compilability classes", and bears strong analogies to the classical theory of complexity, which permits the organization of computational problems according to complexity classes. We develop a novel theory of compilability, called parameterized compilability, which incorporates the notion of parameterization as used in parameterized complexity and permits for refined analysis of compilability.
3576
Collapsibility and Consistency in Quantified Constraint Satisfaction
The concept of consistency has pervaded studies of the constraint satisfiction problem. We introduce two concepts, which are inspired by consistency, for the more general framework of the quantified constraint satisfaction problem (QCSP). We use these concepts to derive, in a uniform fashion, proofs of polynomial-time tractability and corresponding algorithms for certain cases of the QCSP where the types of allowed relations are restricted. We not only unify existing tractability results and algorithms, but also identify new classes of tractable QCSPs.
27175112
Learnability of Relatively Quantified Generalized Formulas
In this paper we study the learning complexity of a vast class of quantifed formulas called Relatively Quantified Generalized Formulas. This class of formulas is parameterized by a set of predicates, called a basis. We give a complete classification theorem, showing that every basis gives rise to quantified formulas that are either polynomially learnable with equivalence queries, or not polynomially predictable with membership queries under some cryptographic assumption. We also provide a simple criteria distinguishing the learnable cases from the non-learnable cases.
2098964
Spam double-funnel: connecting web spammers with advertisers
Spammers use questionable search engine optimization (SEO) techniques to promote their spam links into top search results. In this paper, we focus on one prevalent type of spam - redirection spam - where one can identify spam pages by the third-party domains that these pages redirect traffic to. We propose a five-layer, double-funnel model for describing end-to-end redirection spam, present a methodology for analyzing the layers, and identify prominent domains on each layer using two sets of commercial keywords. one targeting spammers and the other targeting advertisers. The methodology and findings are useful for search engines to strengthen their ranking algorithms against spam, for legitimate website owners to locate and remove spam doorway pages, and for legitimate advertisers to identify unscrupulous syndicators who serve ads on spam pages.
19376839
The Multilevel Classification Problem and a Monotonicity Hint
We introduce and formalize the multilevel classification problem, in which each category can be subdivided into different levels. We analyze the framework in a Bayesian setting using Normal class conditional densities. Within this framework, a natural monotonicity hint converts the problem into a nonlinear programming task, with non-linear constraints. We present Monte Carlo and gradient based techniques for addressing this task, and show the results of simulations. Incorporation of monotonicity yields a systematic improvement in performance.
7847310
The Finite Element Method for Computing the Stationary Distribution of an SRBM in a Hypercube with Applications to Finite Buffer Queueing Networks
This paper proposes an algorithm, referred to as BNAfm (Brownian network analyzer with finite element method), for computing the stationary distribution of a semimartingale reflecting Brownian motion (SRBM) in a hypercube. The SRBM serves as an approximate model of queueing networks with finite buffers. Our BNAfm algorithm is based on the finite element method and an extension of a generic algorithm developed by Dai and Harrison [14]. It uses piecewise polynomials to form an approximate subspace of an infinite-dimensional functional space. The BNAfm algorithm is shown to produce good estimates for stationary probabilities, in addition to stationary moments. This is in contrast to the BNAsm algorithm (Brownian network analyzer with spectral method) of Dai and Harrison [14], which uses global polynomials to form the approximate subspace and which sometimes fails to produce meaningful estimates of these stationary probabilities. Extensive computational experiences from our implementation are reported, which may be useful for future numerical research on SRBMs. A three-station tandem network with finite buffers is presented to illustrate the effectiveness of the Brownian approximation model and our BNAfm algorithm.
4274853
Lifting based discrete wavelet transform architecture for JPEG2000
A lifting based 1-D discrete wavelet transform (DWT) core is proposed. It is re-configurable for 5/3 and 9/7 filters in JPEG2000. Folded architecture is adopted to reduce the hardware cost and achieve the higher hardware utilization. Multiplication is realized in hardwired multiplier with coefficients represented in canonic signed-digit (CSD) form. It is a compact and efficient DWT core for the hardware implementation of JPEG2000 encoder.
9860639
Analysis of parallel algorithms for finding a maximal independent set in a random hypergraph
It is well known 9] that nding a maximal independent set in a graph is in class N C, and 10] that nding a maximal independent set in a hypergraph with xed dimension is in RN C. It is not known whether this latter problem remains in N C when the dimension is part of the input. We will study the problem when the problem instances are randomly chosen. It was shown in 6] that the expected running time of a simple parallel algorithm for nding the lexicographically rst maximal independent set (lfmis) in a random simple graph is logarithmic in the input size. In this paper, we will prove a generalization of this result. We show that if a random k-uniform hypergraph has vertex set f1; 2; : : : ; ng and its edges are chosen independently with probability p from the set of ? n k possible edges, then our algorithm nds the lfmis