In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Multiclass cancer classification on microarray data has provided the feasibility of cancer diagnosis across all of the common malignancies in parallel. Using multiclass cancer feat...
We explore the possibility of recognizing the surface material from a single image with unknown illumination, given the shape of the surface. Model-based PCA is used to create a lo...
The most intuitive memory model for shared-memory multithreaded programming is sequential consistency (SC), but it disallows the use of many compiler and hardware optimizations th...
Daniel Marino, Abhayendra Singh, Todd D. Millstein...