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» Topologically-constrained latent variable models
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JMLR
2010
159views more  JMLR 2010»
13 years 4 months ago
Inference of Sparse Networks with Unobserved Variables. Application to Gene Regulatory Networks
Networks are becoming a unifying framework for modeling complex systems and network inference problems are frequently encountered in many fields. Here, I develop and apply a gener...
Nikolai Slavov
DAC
2007
ACM
14 years 11 months ago
Beyond Low-Order Statistical Response Surfaces: Latent Variable Regression for Efficient, Highly Nonlinear Fitting
The number and magnitude of process variation sources are increasing as we scale further into the nano regime. Today's most successful response surface methods limit us to lo...
Amith Singhee, Rob A. Rutenbar
CVPR
2012
IEEE
12 years 9 days ago
Image categorization using Fisher kernels of non-iid image models
The bag-of-words (BoW) model treats images as an unordered set of local regions and represents them by visual word histograms. Implicitly, regions are assumed to be identically an...
Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia...
EOR
2006
76views more  EOR 2006»
13 years 10 months ago
Regional development assessment: A structural equation approach
We propose a multivariate statistical framework for regional development assessment based on structural equation modelling with latent variables and show how such methods can be c...
Dario Cziráky, Joze Sambt, Joze Rovan, Jaks...
ACCV
2010
Springer
13 years 5 months ago
Latent Gaussian Mixture Regression for Human Pose Estimation
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
Yan Tian, Leonid Sigal, Hernán Badino, Fern...