In this paper, an unsupervised learning algorithm, neighborhood linear embedding (NLE), is proposed to discover the intrinsic structures such as neighborhood relationships, global ...
Shuzhi Sam Ge, Feng Guan, Yaozhang Pan, Ai Poh Loh
Learning temporal causal graph structures from multivariate time-series data reveals important dependency relationships between current observations and histories, and provides a ...
Yan Liu 0002, Alexandru Niculescu-Mizil, Aurelie C...
Hierarchical spatial data structures provide a means for organizing data for efficient processing. Most spatial data structures are optimized for performing queries, such as inters...
Elena Jakubiak Hutchinson, Sarah F. Frisken, Ronal...
Many algorithms and data structures employing hashing have been analyzed under the uniform hashing assumption, i.e., the assumption that hash functions behave like truly random fu...
This paper describes a Hybrid DFT (H-DFT) architecture for low-cost, high quality structural testing in the high volume manufacturing (HVM) environment. This structure efficiently...
David M. Wu, Mike Lin, Subhasish Mitra, Kee Sup Ki...