We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
While information retrieval (IR) and databases (DB) have been developed independently, there have been emerging requirements that both data management and efficient text retrieva...
Jinsuk Kim, Du-Seok Jin, Yunsoo Choi, Chang-Hoo Je...
Abstract--Worldwide health scientists are producing, accessing, analyzing, integrating, and storing massive amounts of digital medical data daily, through observation, experimentat...
Jingshan Huang, Dejing Dou, Lei He, Pat Hayes, Jia...
straction for Information Management Michael Franklin University of California, Berkeley Alon Halevy Google Inc. and U. Washington David Maier Portland State University The develo...
Estimation via sampling out of highly selective join queries is well known to be problematic, most notably in online aggregation. Without goal-directed sampling strategies, samples...