The MAP problem for Bayesian networks is the problem of finding for a set of variables an instantiation of highest posterior probability given the available evidence. The problem is known to be computationally infeasible in general. In this paper, we present a method for preprocessing the MAP problem with the aim of reducing the runtime requirements for its solution. Our method exploits the con...

Constraint satisfaction consistency preprocessing methods are used to reduce search e ort Time and especially space costs limit the amount of preprocess ing that will be cost e ective A new form of con sistency preprocessing neighborhood inverse consis tency can achieve more problem pruning than the usual arc consistency preprocessing in a cost e ective manner There are two basic ideas Common f...

Probably the two best-known exact string matching algorithms are the linear-time algorithm of Knuth, Morris and Pratt (KMP), and the fast on average algorithm of Boyer and Moore (BM). The efficiency of these algorithms is based on using a suitable failure function. When a mismatch occurs in the currently inspected text position, the purpose of a failure function is to tell how many positions th...

When studying complex cognitive tasks using functional magnetic resonance (fMR) imaging one often encounters weak signal responses. These weak responses are corrupted by noise and artifacts of various sources. Preprocessing of the raw data before the application of test statistics helps to extract the signal and thus can vastly improve signal detection. We discuss artifact sources and algorithm...

Genetic algorithms, Evolutionary strategies and many variants of local search algorithms are being applied directly on a fitness function. Such direct search algorithms require minimal knowledge of a problem and can be applied to a wide variety of different domains. This paper suggests to apply a simple mapping on the fitness function – which we refer to as a “preprocessing” step. Any direct se...

For SAT and QBF formulas many techniques are applied in order to reduce/modify the number of variables and clauses of the formula, before the formula is passed to the actual solving algorithm. It is well known that these preprocessing techniques often reduce the computation time of the solver by orders of magnitude. In this paper we generalize different preprocessing techniques for SAT and QBF ...

Orthogonal wavelet bases have been developed using multiple mother wavelet functions. Applying the discrete multiwavelet transform requires the input data to be preprocessed to obtain a more economical decomposition. Four characteristics of a preprocessing method are presented: length, degree, orthogonality and frequency response. A minimal preelter is deened to have length one and highest atta...

This paper presents a novel method for computing visibility in 2.5D environments based on a novel theoretical result: the visibility from a region can be conservatively estimated by computing the visibility from a point using appropriately “shrunk” occluders and occludees. We show how approximate, yet conservative, shrunk objects can be efficiently computed in an urban environment. The techniqu...