This paper presents a novel optimizing compiler for general purpose computation on graphics processing units (GPGPU). It addresses two major challenges of developing high performa...
This article introduces a scheme for clustering complex and linearly non-separable datasets, without any prior knowledge of the number of naturally occurring groups in the data. T...
Although more efficient in computation compared to other tracking approaches such as particle filtering, the kernel-based tracking suffers from the "singularity" problem...
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
Arthur Asuncion, Qiang Liu, Alexander T. Ihler, Pa...
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...