Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
- Robot companions need to be able to constantly acquire knowledge about new objects for instance in order to detect them in the environment. This ability is necessary since it is ...
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
A core problem in data mining is to retrieve data in a easy and human friendly way. Automatically translating natural language questions into SQL queries would allow for the design...