In this paper the authors present a novel method for finding optimal split points for discretization of continuous attributes. Such a method can be used in many data mining techniques for large databases. The method consists of two major steps. In the first step search space is pruned using a bisecting region method that partitions the search space and returns the point with the highest informa...

In many cases programs length’s increase (known as “bloat”, ‘‘fluff” and increasing “structural complexity”) during artificial evolution. We show bloat is not specific to genetic programming and suggest it is inherent in search techniques with discrete variable length representations using simple static evaluation functions. We investigate the bloating characteristics of three non-population an...

We p r e s e n t an algorithm for determining the next best position of a range sensor in 3D space for incrementally recovering an indoor scene. The method works in ve dimensions: the sensor navigates inside the scene, and can be placed at any 3 D position and oriented by a pan-tilt head. The method is based on a mixed exhaustive search and hill climbing optimisation, and outputs the next posit...

We present an algorithm for determining the next best position of a range sensor in 3D space for incrementally recovering an indoor scene. The method works in ve dimensions: the sensor navigates inside the scene, and can be placed at any 3D position and oriented by a pan-tilt head. The method is based on a mixed exhaustive search and hill climbing optimisation, and outputs the next position in ...

A general hill-climbing attack to biometric systems based on a modification of the downhill simplex algorithm is presented. The scores provided by the matcher are used in this approach to adapt iteratively an initial estimate of the attacked template to the specificities of the client being attacked. The proposed attack is evaluated on a competitive feature-based signature verification system o...

This paper introduces an approach to locating dependence structures in a program by searching the space of the powerset of the set of all possible program slices. The paper formulates this problem as a search based software engineering problem. To evaluate the approach, the paper introduces an instance of a search based slicing problem concerned with locating sets of slices that decompose a pro...

This paper addresses the problem of tuning hyperparameters in support vector machine modeling. A Direct Simplex Search (DSS) method, which seeks to evolve hyperparameter values using an empirical error estimate as steering criterion, is proposed and experimentally evaluated on real-world datasets. DSS is a robust hill climbing scheme, a popular derivative-free optimization method, suitable for ...

We introduce a new nearest neighbor search algorithm. The algorithm builds a nearest neighbor graph in an offline phase and when queried with a new point, performs hill-climbing starting from a randomly sampled node of the graph. We provide theoretical guarantees for the accuracy and the computational complexity and empirically show the effectiveness of this algorithm.