We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
Unsupervised vector-based approaches to semantics can model rich lexical meanings, but they largely fail to capture sentiment information that is central to many word meanings and...
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Da...
—In this paper, we address a new unexplored problem - what are the optimal patterns to achieve connected coverage in wireless networks with directional antennas. As their name im...
Zuoming Yu, Jin Teng, Xiaole Bai, Dong Xuan, Weiji...
—Predictive modeling aims at constructing models that predict a target property of an object based on its descriptions. In digital human modeling, it can be applied to predicting...