Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
Abstract—In classical image classification approaches, lowlevel features have been used. But the high dimensionality of feature spaces poses a challenge in terms of feature selec...
Rajeev Agrawal, Changhua Wu, William I. Grosky, Fa...
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...