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» Dynamic Factor Graphs for Time Series Modeling
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FOCS
2008
IEEE
14 years 3 months ago
Mixing Time of Exponential Random Graphs
A plethora of random graph models have been developed in recent years to study a range of problems on networks, driven by the wide availability of data from many social, telecommu...
Shankar Bhamidi, Guy Bresler, Allan Sly
NCA
2002
IEEE
13 years 8 months ago
The Construction of Smooth Models using Irregular Embeddings Determined by a Gamma Test Analysis
One of the key problems in forming a smooth model from input-output data is the determination of which input variables are relevant in predicting a given output. In this paper we ...
Alban P. M. Tsui, Antonia J. Jones, A. Guedes de O...
PAMI
2008
182views more  PAMI 2008»
13 years 8 months ago
Gaussian Process Dynamical Models for Human Motion
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
ICASSP
2011
IEEE
13 years 11 days ago
Modified embedding for multi-regime detection in nonstationary streaming data
Many practical data streams are typically composed of several states known as regimes. In this paper, we invoke phase space reconstruction methods from non-linear time series and ...
Evan Kriminger, José Carlos Príncipe...
BMCBI
2008
135views more  BMCBI 2008»
13 years 8 months ago
Inferring the role of transcription factors in regulatory networks
Background: Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple...
Philippe Veber, Carito Guziolowski, Michel Le Borg...