We address the problem of online de-noising a stream of input points. We assume that the clean data is embedded in a linear subspace. We present two online algorithms for tracking ...
In many graph-based semi-supervised learning algorithms, edge weights are assumed to be fixed and determined by the data points' (often symmetric) relationships in input space...
Abstract. This paper presents a strategy of dynamic user modeling for sketchbased user interface. A user model is defined as an incremental decision tree for a specific user. A dra...
Abstract. Iterative learning is a model of language learning from positive data, due to Wiehagen. When compared to a learner in Gold's original model of language learning from...
Abstract. This paper discusses a machine learning approach for binary classification problems which satisfies the specific requirements of safety-related applications. The approach...