This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
We present a method whereby an embodied agent using visual perception can efficiently create a model of a local indoor environment from its experience of moving within it. Our me...
Grace Tsai, Changhai Xu, Jingen Liu, Benjamin Kuip...
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Background: Identifying protein-protein interactions is fundamental for understanding the molecular machinery of the cell. Proteome-wide studies of protein-protein interactions ar...
Nan Lin, Baolin Wu, Ronald Jansen, Mark Gerstein, ...
Background: The omics fields promise to revolutionize our understanding of biology and biomedicine. However, their potential is compromised by the challenge to analyze the huge da...