Sciweavers

779 search results - page 44 / 156
» Modeling Dependable Systems using Hybrid Bayesian Networks
Sort
View
120
Voted
JETAI
1998
110views more  JETAI 1998»
15 years 2 months ago
Independency relationships and learning algorithms for singly connected networks
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
Luis M. de Campos
132
Voted
PERCOM
2007
ACM
16 years 2 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
141
Voted
IEEECIT
2010
IEEE
15 years 1 months ago
A Learning Spectrum Hole Prediction Model for Cognitive Radio Systems
—In this paper, we present a new spectrum-hole prediction model for cognitive radio (CR) systems based on the IEEE 802.11 wireless local areas networks. We have also analyzed the...
Zhigang Wen, Chunxiao Fan, Xiaoying Zhang, Yuexin ...
147
Voted
SIGCOMM
1996
ACM
15 years 7 months ago
On the Relevance of Long-Range Dependence in Network Traffic
There is much experimental evidence that network traffic processes exhibit ubiquitous properties of self-similarity and long-range dependence, i.e., of correlations over a wide ran...
Matthias Grossglauser, Jean-Chrysostome Bolot
139
Voted
WSC
1997
15 years 4 months ago
A Hybrid Tool for the Performance Evaluation of NUMA Architectures
We present a system for describing and solving closed queuing network models of the memory access performance of NUMA architectures. The system consists of a model description lan...
James Westall, Robert Geist