Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
Background: While multiple alignment is the first step of usual classification schemes for biological sequences, alignment-free methods are being increasingly used as alternatives...
Eduardo Corel, Florian Pitschi, Ivan Laprevotte, G...
We propose a new multiple instance learning (MIL) algorithm to learn image categories. Unlike existing MIL algorithms, in which the individual instances in a bag are assumed to be...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jin...
Concepts are an essential language feature for generic programming in the large. Concepts allow for succinct expression of constraints on type parameters of generic algorithms, en...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...