Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
We present a method for dependency grammar induction that utilizes sparse annotations of semantic relations. This induction set-up is attractive because such annotations provide u...
In many developing countries such as India and China, low educational levels often hinder economic empowerment. In this paper, we argue that mobile learning games can play an impo...
Data quality is critical for many information-intensive applications. One of the best opportunities to improve data quality is during entry. USHER provides a theoretical, data-dri...
Kuang Chen, Joseph M. Hellerstein, Tapan S. Parikh
Abstract. A combinatorial random variable is a discrete random variable defined over a combinatorial set (e.g., a power set of a given set). In this paper we introduce combinatoria...
Ron Bekkerman, Mehran Sahami, Erik G. Learned-Mill...