We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
Model-based image interpretation extracts high-level information from images using a priori knowledge about the object of interest. The computational challenge in model fitting is...
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
This paper deals with the problem of making predictions in the online mode of learning where the dependence of the outcome yt on the signal xt can change with time. The Aggregating...
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...