In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
— In many applications involving the multiple criteria optimal decision making, users may often want to make a personal trade-off among all optimal solutions. As a key feature, t...
Xuemin Lin, Ying Zhang, Wenjie Zhang, Muhammad Aam...
Motivated by improvements in constraint-solving technology and by the increase of routinely available computational power, partial-program synthesis is emerging as an effective a...
Feature selection is fundamental to knowledge discovery from massive amount of high-dimensional data. In an effort to establish theoretical justification for feature selection al...
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...