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» A Temporal Consensus Model
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NIPS
1998
15 years 8 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
JMLR
2010
103views more  JMLR 2010»
15 years 1 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
CVPR
2003
IEEE
16 years 8 months ago
Video-Based Face Recognition Using Adaptive Hidden Markov Models
While traditional face recognition is typically based on still images, face recognition from video sequences has become popular recently. In this paper, we propose to use adaptive...
Xiaoming Liu 0002, Tsuhan Chen
ICIP
2006
IEEE
16 years 8 months ago
Detecting Occlusion for Hidden Markov Modeled Shapes
In this paper, we present a novel occlusion detection scheme for hidden Markov modeled shapes. First, hidden Markov model (HMM) is built using multiple examples of the shape. A re...
Ninad Thakoor, Sungyong Jung, Jean Gao
CADE
2002
Springer
16 years 7 months ago
Lazy Theorem Proving for Bounded Model Checking over Infinite Domains
Abstract. We investigate the combination of propositional SAT checkers with domain-specific theorem provers as a foundation for bounded model checking over infinite domains. Given ...
Harald Rueß, Leonardo Mendonça de Mou...