We propose the k-representative regret minimization query (k-regret) as an operation to support multi-criteria decision making. Like top-k, the k-regret query assumes that users h...
Danupon Nanongkai, Atish Das Sarma, Ashwin Lall, R...
Given a set of multi-dimensional points, the skyline contains the best points according to any preference function that is monotone on all axes. In practice, applications that req...
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Tsochantaridis et al. (2005) proposed two formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling has been extensivel...
Abstract-- This work presents a novel index structure, MHRtree, for efficiently answering approximate string match queries in large spatial databases. The MHR-tree is based on the ...
Bin Yao, Feifei Li, Marios Hadjieleftheriou, Kun H...