The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due ...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, T...
We suggest a new heuristic for solving unconstrained continuous optimization problems. It is based on a generalized version of the variable neighborhood search metaheuristic. Diff...
Nenad Mladenovic, Milan Drazic, Vera Kovacevic-Vuj...
A major development in qualitative model checking was the jump to verifying properties of source code directly, rather than requiring a separately specified model. We describe an...
Background: The functional selection and three-dimensional structural constraints of proteins in nature often relates to the retention of significant sequence similarity between p...
We present a new method for the incremental training of multiclass Support Vector Machines that provides computational efficiency for training problems in the case where the trai...