This paper reviews probabilistic approaches to rough sets in granulation, approximation, and rule induction. The Shannon entropy function is used to quantitatively characterize pa...
We suggest a local hybrid approximation scheme based on polynomials and radial basis functions, and use it to modify the scattered data fitting algorithm of [7]. Similar to that a...
In plant pathology, in particular, and plant science, in general, experiments are often conducted to determine disease and related responses of plants to various treatments. Typic...
Arne C. Bathke, Solomon W. Harrar, Laurence V. Mad...
Sociologists, demographers, and economists often use the index of dissimilarity, D, to describe the extent of racial, ethnic, spatial, or areal dissimilarity (or segregation) of d...
Madhuri S. Mulekar, John C. Knutson, Jyoti A. Cham...
This paper proposes a method for computing fast approximations to support vector decision functions in the field of object detection. In the present approach we are building on an...
Abstract. We look for the approximation of exp(A1 + A2) by a product in form exp(x1A1) exp(y1A2) · · · exp(xnA1) exp(ynA2). We specially are interested in minimal approximations...
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximatin...
In many different application areas, e.g. space observation systems or engineering systems of world-wide operating companies, there is a need for an efficient distributed intersect...
Hans-Peter Kriegel, Peter Kunath, Martin Pfeifle, ...
We consider approximation algorithms for non-uniform buy-at-bulk network design problems. The first nontrivial approximation algorithm for this problem is due to Charikar and Kar...
Chandra Chekuri, Mohammad Taghi Hajiaghayi, Guy Ko...