26 search results - page 2 / 6 » Sparse Gaussian graphical models with unknown block structur... |
JMLR
2010
12 years 11 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
CORR
2011
Springer
12 years 12 months ago
2011
Springer
We propose a factor-graph-based approach to joint channel-estimationand-decoding of bit-interleaved coded orthogonal frequency division multiplexing (BICM-OFDM). In contrast to ex...
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
We present multi-task structure learning for Gaussian graphical models. We discuss uniqueness and boundedness of the optimal solution of the maximization problem. A block coordina...
CORR
2008
Springer
13 years 5 months ago
2008
Springer
Abstract--Interior-point methods are state-of-the-art algorithms for solving linear programming (LP) problems with polynomial complexity. Specifically, the Karmarkar algorithm typi...
ICIP
2009
IEEE
13 years 2 months ago
2009
IEEE
A novel framework for spatially estimating unknown image data is presented. Common applications include inpainting, concealment of transmission errors, prediction in video coding,...