We describe a discriminatively trained sequence alignment model based on the averaged perceptron. In common with other approaches to sequence modeling using perceptrons, and in co...
Collaborative and content-based filtering are two paradigms that have been applied in the context of recommender systems and user preference prediction. This paper proposes a nove...
Abstract. In this paper we investigate the way of improving the performance of a Named Entity Extraction (NEE) system by applying machine learning techniques and corpus transformat...
Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can...
Qinbao Song, Martin J. Shepperd, Xiangru Chen, Jun...
Our focus is on designing adaptable agents for highly dynamic environments. Wehave implementeda reinforcement learning architecture as the reactive componentof a twolayer control ...