We describe computationally efficient methods for learning mixtures in which each component is a directed acyclic graphical model (mixtures of DAGs or MDAGs). We argue that simple...
Bo Thiesson, Christopher Meek, David Maxwell Chick...
: A computer program has been developed to aid the analysis of molecular dynamics trajectories. The program is tuned for macromolecular large-scale problems and supports features s...
We consider an active learning game within a transductive learning model. A major problem with many active learning algorithms is that an unreliable current hypothesis can mislead...
Reconfigurable software is highly desired for automated machine tool control systems for low-cost products and short time to market. In this paper, we propose a software architectu...
We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...