Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
Powerful servers for computation and storage, high-speed networking resources, and high-performance 3D graphics workstation, which are typically available in scientific research e...
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
As part of the Illinois Digital Library Initiative (DLI) project we developed “scalable semantics” technologies. These statistical techniques enabled us to index large collect...
Yi-Ming Chung, Qin He, Kevin Powell, Bruce R. Scha...
As the field of human-computer interaction matures, the need for proven, dependable engineering processes for interface development becomes apparent. Our continuing work in develo...
Jason Chong Lee, Christa M. Chewar, D. Scott McCri...