Active learning (AL) is an increasingly popular strategy for mitigating the amount of labeled data required to train classifiers, thereby reducing annotator effort. We describe ...
Byron C. Wallace, Kevin Small, Carla E. Brodley, T...
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Address re-mapping techniques in so-called active memory systems have been shown to dramatically increase the performance of applications with poor cache and/or communication beha...
Dhiraj D. Kalamkar, Mainak Chaudhuri, Mark Heinric...
In many data mining applications, online labeling feedback is only available for examples which were predicted to belong to the positive class. Such applications include spam filt...
Many document collections are by nature dynamic, evolving as the topics or events they describe change. The goal of temporal text mining is to discover bursty patterns and to ident...