In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Many of today's best classification results are obtained by combining the responses of a set of base classifiers to produce an answer for the query. This paper explores a nov...
The detection of faces in images is fundamentally a rare event detection problem. Cascade classifiers provide an efficient computational solution, by leveraging the asymmetry in t...
Aiming at the problem when both positive and negative training set are enormous, this paper proposes a novel Matrix-Structural Learning (MSL) method, as an extension to Viola and ...
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...