Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
High-dimensional data poses a severe challenge for data mining. Feature selection is a frequently used technique in preprocessing high-dimensional data for successful data mining....
We present an efficient feature selection algorithm for computer aided detection (CAD) computed tomographic (CT) colonography. The algorithm 1) determines an appropriate piecewise...
Jiang Li, Jianhua Yao, Ronald M. Summers, Nicholas...
Conditional log-linear models are a commonly used method for structured prediction. Efficient learning of parameters in these models is therefore an important problem. This paper ...
Amir Globerson, Terry Koo, Xavier Carreras, Michae...