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 ...
Active learning has been successfully applied to many natural language processing tasks for obtaining annotated data in a cost-effective manner. We propose several extensions to an...
Abstract. In this work, we apply and evaluate a machine-learningbased system to Portuguese clause identification. To the best of our knowledge, this is the first machine-learning-b...
A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
Background: Use of alternative gene promoters that drive widespread cell-type, tissue-type or developmental gene regulation in mammalian genomes is a common phenomenon. Chromatin ...
Ravi Gupta, Priyankara Wikramasinghe, Anirban Bhat...