Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
This paper presents an active learning approach to the problem of systematic noise inference and noise elimination, specifically the inference of Associated Corruption (AC) rules...
Self-training is a semi-supervised learning algorithm in which a learner keeps on labeling unlabeled examples and retraining itself on an enlarged labeled training set. Since the s...
Synchronous Data Flow Graphs (SDFGs) are a very useful means for modeling and analyzing streaming applications. Some performance indicators, such as throughput, have been studied b...
Amir Hossein Ghamarian, Sander Stuijk, Twan Basten...
Decision Support System (DSS) workloads are known to be one of the most time-consuming database workloads that processes large data sets. Traditionally, DSS queries have been acce...