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DSP
2006
13 years 4 months ago
Adaptive multi-modality sensor scheduling for detection and tracking of smart targets
This paper considers the problem of sensor scheduling for the purposes of detection and tracking of "smart" targets. Smart targets are targets that can detect when they ...
Christopher M. Kreucher, Doron Blatt, Alfred O. He...
AIPS
2000
13 years 6 months ago
On-line Scheduling via Sampling
1 We consider the problem of scheduling an unknown sequence of tasks for a single server as the tasks arrive with the goal off maximizing the total weighted value of the tasks serv...
Hyeong Soo Chang, Robert Givan, Edwin K. P. Chong
IWDC
2004
Springer
153views Communications» more  IWDC 2004»
13 years 10 months ago
APPLE: A Novel P2P Based e-Learning Environment
With the rapid development of information technology, dramatic changes have been taken place in the fundamental ways that people acquire and disseminate knowledge. Various e-Learni...
Hai Jin, Zuoning Yin, Xudong Yang, Fucheng Wang, J...
AIR
2006
107views more  AIR 2006»
13 years 5 months ago
Just enough learning (of association rules): the TAR2 "Treatment" learner
Abstract. An over-zealous machine learner can automatically generate large, intricate, theories which can be hard to understand. However, such intricate learning is not necessary i...
Tim Menzies, Ying Hu
KDD
2005
ACM
147views Data Mining» more  KDD 2005»
13 years 10 months ago
Combining proactive and reactive predictions for data streams
Mining data streams is important in both science and commerce. Two major challenges are (1) the data may grow without limit so that it is difficult to retain a long history; and (...
Ying Yang, Xindong Wu, Xingquan Zhu