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» Learning Dynamic Bayesian Networks
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EMNLP
2009
14 years 10 months ago
On the Use of Virtual Evidence in Conditional Random Fields
Virtual evidence (VE), first introduced by (Pearl, 1988), provides a convenient way of incorporating prior knowledge into Bayesian networks. This work generalizes the use of VE to...
Xiao Li
105
Voted
BMCBI
2008
107views more  BMCBI 2008»
15 years 27 days ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng
123
Voted
CCGRID
2006
IEEE
15 years 6 months ago
INTCTD: A Peer-to-Peer Approach for Intrusion Detection
In this paper we propose a peer-to-peer (P2P) prototype (INTCTD) for intrusion detection over an overlay network. INTCTD is a distributed system based on neural networks for detec...
Catalin Dumitrescu
127
Voted
ICANN
2005
Springer
15 years 6 months ago
A Hardware/Software Framework for Real-Time Spiking Systems
Abstract. One focus of recent research in the field of biologically plausible neural networks is the investigation of higher-level functions such as learning, development and modu...
Matthias Oster, Adrian M. Whatley, Shih-Chii Liu, ...
87
Voted
CEC
2007
IEEE
15 years 7 months ago
Evolving neuromodulatory topologies for reinforcement learning-like problems
— Environments with varying reward contingencies constitute a challenge to many living creatures. In such conditions, animals capable of adaptation and learning derive an advanta...
Andrea Soltoggio, Peter Dürr, Claudio Mattius...