Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
The conventional weighted aggregation method is extended to realize multi-objective optimization. The basic idea is that systematically changing the weights during evolution will l...
In this paper we analyze a quasi-Monte Carlo method for solving systems of linear algebraic equations. It is well known that the convergence of Monte Carlo methods for numerical in...
In this paper we address the question: Is water-filling appropriate for watermarking? The water-filling paradigm is a traditional solution to the capacity maximization of parall...
Abstract. In this paper we provide a theoretical framework for estimating the size of the intersection join between two line segment datasets (e.g., roads, railways, utilities). Fo...