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» Learning Nonlinear Dynamical Systems Using an EM Algorithm
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88
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GIS
2009
ACM
15 years 1 months ago
Dynamic network data exploration through semi-supervised functional embedding
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
Alexei Pozdnoukhov
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
14 years 1 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
AUTOMATICA
2008
167views more  AUTOMATICA 2008»
14 years 9 months ago
Stability and robustness analysis of nonlinear systems via contraction metrics and SOS programming
A wide variety of stability and performance questions about linear dynamical systems can be reformulated as convex optimization problems involving linear matrix inequalities (LMIs...
Erin M. Aylward, Pablo A. Parrilo, Jean-Jacques E....
JMLR
2006
143views more  JMLR 2006»
14 years 9 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth
82
Voted
AI
2008
Springer
15 years 4 months ago
Using Unsupervised Learning for Network Alert Correlation
Alert correlation systems are post-processing modules that enable intrusion analysts to find important alerts and filter false positives efficiently from the output of Intrusion...
Reuben Smith, Nathalie Japkowicz, Maxwell Dondo, P...