We propose a probabilistic, generative account of configural learning phenomena in classical conditioning. Configural learning experiments probe how animals discriminate and gener...
Aaron C. Courville, Nathaniel D. Daw, David S. Tou...
In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...
The requirements, design principles, and statistical testing approaches of uniform random number generators for simulation are briefly surveyed. An objectoriented random number pa...
Parameters of statistical distributions that are input to simulations are typically not known with certainty. For existing systems, or variations on existing systems, they are oft...
We present methods for learning and tracking human motion in video. We estimate a statistical model of typical activities from a large set of 3D periodic human motion data by segm...
Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black...