Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
This paper presents an innovative model of a program’s internal behavior over a set of test inputs, called the probabilistic program dependence graph (PPDG), that facilitates pr...
In this paper, we propose an iterative similarity propagation approach to explore the inter-relationships between Web images and their textual annotations for image retrieval. By ...
Insufficient training data is one of the major problems in neural network learning, because it leads to poor learning performance. In order to enhance an intelligent learning proc...
This paper deals with an extension of one-dimensional Clenshaw–Curtis quadrature rule to Rd ; d P 2 on a convex domain. As one of its applications, we apply this quadrature rule...