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JMLR
2010
140views more  JMLR 2010»
14 years 11 months ago
Learning Non-Stationary Dynamic Bayesian Networks
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Joshua W. Robinson, Alexander J. Hartemink
EWSN
2004
Springer
16 years 3 months ago
Structured Communication in Single Hop Sensor Networks
Abstract. We propose a model for communication in single-hop wireless sensor networks and define and evaluate the performance of a robust, energy balanced protocol for a powerful a...
Amol Bakshi, Viktor K. Prasanna
IJCNN
2000
IEEE
15 years 8 months ago
The Growing Hierarchical Self-Organizing Map
In this paper we present the growing hierarchical self-organizing map. This dynamically growing neural network model evolves into a hierarchical structure according to the requirem...
Michael Dittenbach, Dieter Merkl, Andreas Rauber
ICML
2006
IEEE
16 years 4 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
WCNC
2008
IEEE
15 years 10 months ago
Integrated Source-Channel Decoding for Correlated Data-Gathering Sensor Networks
Abstract— This paper explores integrated source-channel decoding, driven by wireless sensor network applications where correlated information acquired by the network is gathered ...
Sheryl L. Howard, Paul G. Flikkema