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» Learning Nonlinear Dynamical Systems Using an EM Algorithm
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GIS
2009
ACM
15 years 7 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 7 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
131
Voted
AUTOMATICA
2008
167views more  AUTOMATICA 2008»
15 years 3 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....
144
Voted
JMLR
2006
143views more  JMLR 2006»
15 years 3 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
133
Voted
AI
2008
Springer
15 years 10 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...