Abstract. Automatic pattern classifiers that allow for on-line incremental learning can adapt internal class models efficiently in response to new information without retraining fr...
The performance of on-line algorithms for learning dichotomies is studied. In on-line learning, the number of examples P is equivalent to the learning time, since each example is ...
Abstract. Autonomous learning systems of significant complexity often consist of several interacting modules or agents. These modules collaborate to produce a system which, when vi...
We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
Fei-Fei Li 0002, Pietro Perona, California Institu...
In this paper we consider the problem of actively learning the mean values of distributions associated with a finite number of options (arms). The algorithms can select which opti...