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» Learning from Time-Changing Data with Adaptive Windowing
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KAIS
2007
113views more  KAIS 2007»
13 years 7 months ago
CPU load shedding for binary stream joins
We present an adaptive load shedding approach for windowed stream joins. In contrast to the conventional approach of dropping tuples from the input streams, we explore the concept ...
Bugra Gedik, Kun-Lung Wu, Philip S. Yu, Ling Liu
CVPR
2010
IEEE
14 years 1 months ago
Multi-Target Tracking by On-Line Learned Discriminative Appearance Models
We present an approach for online learning of discriminative appearance models for robust multi-target tracking in a crowded scene from a single camera. Although much progress has...
Cheng-Hao Kuo, Chang Huang, Ram Nevatia
ICASSP
2011
IEEE
12 years 11 months ago
A sliding-window online fast variational sparse Bayesian learning algorithm
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor
TKDE
2008
169views more  TKDE 2008»
13 years 7 months ago
A Cost-Based Approach to Adaptive Resource Management in Data Stream Systems
Data stream management systems need to control their resources adaptively since stream characteristics and query workload may vary over time. In this paper we investigate an approa...
Michael Cammert, Jürgen Krämer, Bernhard...
SIGMOD
2008
ACM
138views Database» more  SIGMOD 2008»
14 years 7 months ago
Sampling time-based sliding windows in bounded space
Random sampling is an appealing approach to build synopses of large data streams because random samples can be used for a broad spectrum of analytical tasks. Users are often inter...
Rainer Gemulla, Wolfgang Lehner