Privacy-preserving decision tree mining is an important problem that has yet to be thoroughly understood. In fact, the privacypreserving decision tree mining method explored in the...
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
Background: In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changi...
J. Lynn Fink, Pablo Fernicola, Rahul Chandran, Sav...
We cast name discrimination as a problem in clustering short contexts. Each occurrence of an ambiguous name is treated independently, and represented using second?order context vec...
We present an approach for automatic detection of topic change. Our approach is based on the analysis of statistical features of topics in time-sliced corpora and their dynamics ov...