Abstract. In multi-instance learning, each example is described by a bag of instances instead of a single feature vector. In this paper, we revisit the idea of performing multi-ins...
A common problem in applied mathematics is that of finding a function in a Hilbert space with prescribed best approximations from a finite number of closed vector subspaces. In ...
This paper proposes an efficient online method that trains a classifier with many conjunctive features. We employ kernel computation called kernel slicing, which explicitly consid...
In the task of mispronunciation detection, the cross-speaker degradation and some other confusing nuisances are the challenging problems demanding prompt solution. In this paper, ...
A method dealing with recognition of partially occluded and affine transformed binary objects is presented. The method is designed for objects with smooth curved boundary. It divi...