—In this paper, we propose a new nonlinear classier based on a generalized Choquet integral with signed fuzzy measures to enhance the classification power by capturing all possib...
Many of the current radiosity algorithms create a piecewise constant approximation to the actual radiosity. Through interpolation and extrapolation, a continuous solution is obtai...
This paper aims to conduct a study on the listwise approach to learning to rank. The listwise approach learns a ranking function by taking individual lists as instances and minimi...
This paper presents a problem-independent framework that uni es various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not ne...
We introduce the concept of knowledge states; many well-known algorithms can be viewed as knowledge state algorithms. The knowledge state approach can be used to to construct comp...
Wolfgang W. Bein, Lawrence L. Larmore, John Noga, ...