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» Importance Sampling for Continuous Time Bayesian Networks
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INFOCOM
1997
IEEE
15 years 4 months ago
Proactive Network Fault Detection
The increasing role of communication networks in today’s society results in a demand for higher levels of network availability and reliability. At the same time, fault managemen...
Cynthia S. Hood, Chuanyi Ji
ICCV
2003
IEEE
16 years 1 months ago
Real-Time Simultaneous Localisation and Mapping with a Single Camera
Ego-motion estimation for an agile single camera moving through general, unknown scenes becomes a much more challenging problem when real-time performance is required rather than ...
Andrew J. Davison
EMNLP
2010
14 years 9 months ago
Training Continuous Space Language Models: Some Practical Issues
Using multi-layer neural networks to estimate the probabilities of word sequences is a promising research area in statistical language modeling, with applications in speech recogn...
Hai Son Le, Alexandre Allauzen, Guillaume Wisniews...
SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
15 years 12 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal
FPGA
2010
ACM
232views FPGA» more  FPGA 2010»
14 years 12 months ago
High-throughput bayesian computing machine with reconfigurable hardware
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Mingjie Lin, Ilia Lebedev, John Wawrzynek