Principal curves have been defined as "self consistent" smooth curves which pass through the "middle" of a d-dimensional probability distribution or data cloud...
This work provides a generalization of the traditional response surface methodology (RSM) that can be applied to complex, multi-objective simulation studies. These problems involv...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
In this paper, we describe a set of 3D and 4D visualization tools and techniques for CORIE, a complex environmental observation and forecasting system (EOFS) for the Columbia Rive...
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...