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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
16 years 5 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2009
ACM
159views Data Mining» more  KDD 2009»
16 years 5 months ago
Adapting the right measures for K-means clustering
Clustering validation is a long standing challenge in the clustering literature. While many validation measures have been developed for evaluating the performance of clustering al...
Junjie Wu, Hui Xiong, Jian Chen
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
16 years 5 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
PODS
2009
ACM
112views Database» more  PODS 2009»
16 years 5 months ago
Optimal sampling from sliding windows
APPEARED IN ACM PODS-2009. A sliding windows model is an important case of the streaming model, where only the most "recent" elements remain active and the rest are disc...
Vladimir Braverman, Rafail Ostrovsky, Carlo Zaniol...
MOBIHOC
2009
ACM
16 years 5 months ago
Admission control and scheduling for QoS guarantees for variable-bit-rate applications on wireless channels
Providing differentiated Quality of Service (QoS) over unreliable wireless channels is an important challenge for supporting several future applications. We analyze a model that h...
I-Hong Hou, P. R. Kumar