In this paper we present sQueezeBF, an effective preprocessor for QBFs that combines various techniques for eliminating variables and/or clauses. In particular sQueezeBF combines (i) variable elimination by Q-resolution and equality reduction, and (ii) clause simplification via subsumption and self-subsumption resolution. The experimental analysis shows that sQueezeBF can produce significant re...

Preprocessing algorithms can dramatically improve the performance of even the most efficient SAT solvers on many problem instances [8]. Such algorithms simplify the formula by various means, including the deduction of necessary assignments, the addition of implied clauses, the deletion of redundant clauses, and the identification of equivalent literals. A number of preprocessors have been made ...

Techniques for the preprocessing of (not-necessarily convex) quadratic programs are discussed. Most of the procedures extend known ones from the linear to quadratic cases, but a few new preprocessing techniques are introduced. The implementation aspects are also discussed. Numerical results are finally presented to indicate the potential of the resulting code, both for linear and quadratic prob...

We present an interactive web tool for preprocessing microarray gene expression data. It analyses the data, suggests the most appropriate transformations and proceeds with them after user agreement. The normal preprocessing steps include scale transformations, management of missing values, replicate handling, flat pattern filtering and pattern standardization and they are required before perfor...

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...