Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
The Drosophila gene expression pattern images document the spatial and temporal dynamics of gene expression and they are valuable tools for explicating the gene functions, interac...
Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, ...
In POPL 2002, Petrank and Rawitz showed a universal result-finding optimal data placement is not only NP-hard but also impossible to approximate within a constant factor if P = NP...
Given a set of model graphs D and a query graph q, containment search aims to find all model graphs g D such that q contains g (q g). Due to the wide adoption of graph models, f...
Chen Chen, Xifeng Yan, Philip S. Yu, Jiawei Han, D...
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...