8 search results - page 1 / 2 » Partially Observed Maximum Entropy Discrimination Markov Net... |
NIPS
2008
13 years 6 months ago
2008
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
PERCOM
2007
ACM
14 years 4 months ago
2007
ACM
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
ICML
2008
IEEE
14 years 5 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...
CVIU
2006
13 years 4 months ago
2006
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
—We aim to characterize the maximum link throughput of a multi-channel opportunistic communication system. The states of these channels evolve as independent and identically dist...