Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensemb...
Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bo...
Abstract. Recent results on robust density-based clustering have indicated that the uncertainty associated with the actual measurements can be exploited to locate objects that are ...
Abstract—We propose a robust fitting framework, called Adaptive Kernel-Scale Weighted Hypotheses (AKSWH), to segment multiplestructure data even in the presence of a large number...
Abstract. Software systems nowadays are becoming increasingly complex and vulnerable to all sorts of failures and attacks. There is a rising need for robust self-repairing systems ...
Thomas Meyer, Daniel Schreckling, Christian F. Tsc...
Abstract. Data centric languages, such as recursive rule based languages, have been proposed to program distributed applications over networks. They simplify greatly the code, whic...