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JMLR
2006
169views more  JMLR 2006»
15 years 6 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
JSAC
2006
112views more  JSAC 2006»
15 years 6 months ago
Network Kriging
ABSTRACT. Network service providers and customers are often concerned with aggregate performance measures that span multiple network paths. Unfortunately, forming such network-wide...
David B. Chua, Eric D. Kolaczyk, Mark Crovella
NPL
2006
172views more  NPL 2006»
15 years 6 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
TMC
2008
120views more  TMC 2008»
15 years 6 months ago
Mitigating Performance Degradation in Congested Sensor Networks
Data generated in wireless sensor networks may not all be alike: some data may be more important than others and hence may have different delivery requirements. In this paper, we a...
Raju Kumar, Riccardo Crepaldi, Hosam Rowaihy, Albe...
EWSN
2009
Springer
16 years 7 months ago
Flow-Based Real-Time Communication in Multi-Channel Wireless Sensor Networks
As many radio chips used in today's sensor mote hardware can work at different frequencies, several multi-channel communication protocols have recently been proposed to improv...
Xiaodong Wang, Xiaorui Wang, Xing Fu, Guoliang Xin...