We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. This paper aims to shed ...
In this paper we present a system that combines the benefits of 3D deformable models and level set methods for medical volume segmentation. Our 3D deformable model is a very comp...
Derek R. Magee, Andrew J. Bulpitt, Elizabeth Berry
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructe...