Abstract. Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the re...
Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, ...
We describe two market-inspired approaches to propositional satisfiability. Whereas a previous market-inspired approach exhibited extremely slow performance, we find that variatio...
William E. Walsh, Makoto Yokoo, Katsutoshi Hirayam...
This paper presents a new method — the Time-delay Added Evolutionary Forecasting (TAEF) method — for time series prediction which performs an evolutionary search of the minimu...
Tiago A. E. Ferreira, Germano C. Vasconcelos, Paul...
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
A method is presented for segmentation of anatomical structures that incorporates prior information about shape. The method iteratively applies steps which find object’s border ...