30 search results - page 3 / 6 » Map approach to learning sparse Gaussian Markov networks |
KES
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. A new approach is proposed to recover the relative magnitude of Gaussian curvature from three shading images using neural network. Under the assumption that the test obje...
ICML
2008
IEEE
14 years 6 months ago
2008
IEEE
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
DCC
2006
IEEE
14 years 4 months ago
2006
IEEE
This paper proposes a framework for joint source-channel decoding of Markov sequences that are coded by a fixed-rate multiple description quantizer (MDQ), and transmitted via a lo...
CORR
2011
Springer
13 years 8 days ago
2011
Springer
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing informa...
JMLR
2008
13 years 5 months ago
2008
We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...