We present an optimization algorithm that combines active learning and locally-weighted regression to find extreme points of noisy and complex functions. We apply our algorithm to...
Abstract. Approximation has been identified as a potential way of reducing the complexity of logical reasoning. Here we explore approximation for speeding up instance retrieval in...
Current object-oriented formalisms, such as UML, focus on describing class models and use instance models only for depicting scenarios. Little attention is being devoted to defini...
A major difficulty in evaluating incomplete local search style algorithms for constraint satisfaction problems is the need for a source of hard problem instances that are guarante...
Dimitris Achlioptas, Carla P. Gomes, Henry A. Kaut...
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...