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DIS
2006
Springer
14 years 1 months ago
Kalman Filters and Adaptive Windows for Learning in Data Streams
We study the combination of Kalman filter and a recently proposed algorithm for dynamically maintaining a sliding window, for learning from streams of examples. We integrate this i...
Albert Bifet, Ricard Gavaldà
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
14 years 4 months ago
Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
Debprakash Patnaik, Srivatsan Laxman, Naren Ramakr...
OSDI
2004
ACM
14 years 10 months ago
ksniffer: Determining the Remote Client Perceived Response Time from Live Packet Streams
As dependence on the World Wide Web continues to grow, so does the need for businesses to have quantitative measures of the client perceived response times of their Web services. ...
David P. Olshefski, Jason Nieh, Erich M. Nahum
SIGMOD
2006
ACM
131views Database» more  SIGMOD 2006»
14 years 9 months ago
An automatic construction and organization strategy for ensemble learning on data streams
As data streams are gaining prominence in a growing number of emerging application domains, classification on data streams is becoming an active research area. Currently, the typi...
Yi Zhang, Xiaoming Jin
DEXA
2009
Springer
151views Database» more  DEXA 2009»
14 years 4 months ago
Detecting Projected Outliers in High-Dimensional Data Streams
Abstract. In this paper, we study the problem of projected outlier detection in high dimensional data streams and propose a new technique, called Stream Projected Ouliter deTector ...
Ji Zhang, Qigang Gao, Hai H. Wang, Qing Liu, Kai X...