Preprocessing SAT instances can reduce their size considerably. We combine variable elimination with subsumption and selfsubsuming resolution, and show that these techniques not only shrink the formula further than previous preprocessing efforts based on variable elimination, but also decrease runtime of SAT solvers substantially for typical industrial SAT problems. We discuss critical implemen...

New feature selection algorithms for linear threshold functions are described which combine backward elimination with an adaptive regularization method. This makes them particularly suitable to the classification of microarray expression data, where the goal is to obtain accurate rules depending on few genes only. Our algorithms are fast and easy to implement, since they center on an incrementa...

In the last couple of years it has been realized that Gaussian elimination for sparse matrices arising from certain elliptic PDEs can be done in O(n log(1/ )) flops, where n is the number of unknowns and is a user-specified tolerance [Chandrasekaran and Gu]. The resulting solver will also be backward stable with an error of O( ). The techniques used to achieve this speedup has some commonality ...

A novel multibending backward-oblique viewing duodenoscope was developed to overcome the difficult technical aspect of deep cannulation into the bile duct during endoscopic retrograde cholangiopancreatography (ERCP). The aim of the present study was to evaluate the initial experience of a novel multibending backward-oblique viewing duodenoscope (M-D scope) for ERCP. This was a retrospective rev...

A new block extended backward differentiation formula suitable for the integration of stiff initial value problems is derived. The procedure used involves the use of an extra future point which helps in improving the performance of an existing block backward differentiation formula. The method approximates the solution at 3 points simultaneously at each step. Accuracy and stability properties o...

Prediction intervals in State Space models can be obtained by assuming Gaussian innovations and using the prediction equations of the Kalman filter, where the true parameters are substituted by consistent estimates. This approach has two limitations. First, it does not incorporate the uncertainty due to parameter estimation. Second, the Gaussianity assumption of future innovations may be inaccu...

Generalizing the novel clause elimination procedures developed in [1], we introduce explicit (CCE), hidden (HCCE), and asymmetric (ACCE) variants of a procedure that eliminates covered clauses from CNF formulas. We show that these procedures are more effective in reducing CNF formulas than the respective variants of blocked clause elimination, and may hence be interesting as new preprocessing/s...

In this paper, we consider three different search strategies for a cut-free sequent system formalizing orthologic, and estimate the respective search spaces. Applying backward search, there are classes of formulae for which both the minimal proof length and the search space are exponential. In a combined forward and backward approach, all proofs are polynomial, but the potential search space re...

In this paper we propose a robust genetic algorithm for the multi-mode resourceconstrained project scheduling problem. We present a new representation for the solutions to this problem, which includes an additional bit indicating the scheduling scheme used to construct the schedule, forward or backward. Moreover, we have developed new genetic operators which operate over this representation, ex...

Consider linear prediction models where the target function is a sparse linear combination of a set of basis functions. We are interested in the problem of identifying those basis functions with non-zero coefficients and reconstructing the target function from noisy observations. Two heuristics that are widely used in practice are forward and backward greedy algorithms. First, we show that neit...