Real-world databases often contain syntactic and semantic errors, in spite of integrity constraints and other safety measures incorporated into modern DBMSs. We present ERACER, an...
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
We have been developing a data mining (i.e., knowledge discovery) framework, MADAM ID, for Mining Audit Data for Automated Models for Intrusion Detection [LSM98, LSM99b, LSM99a]. ...
Processing and analyzing large volumes of data plays an increasingly important role in many domains of scienti c research. High-level language and compiler support for developing ...
We describe a method to improve detection of disease outbreaks in pre-diagnostic time series data. The method uses multiple forecasters and learns the linear combination to minimi...