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» Logical Hidden Markov Models
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ICML
2005
IEEE
16 years 4 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
149
Voted
ICML
2000
IEEE
16 years 4 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
126
Voted
TKDE
2010
150views more  TKDE 2010»
15 years 2 months ago
Prospective Infectious Disease Outbreak Detection Using Markov Switching Models
—Accurate and timely detection of infectious disease outbreaks provides valuable information which can enable public health officials to respond to major public health threats in...
Hsin-Min Lu, Daniel Zeng, Hsinchun Chen
AAAI
2008
15 years 6 months ago
Hybrid Markov Logic Networks
Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
Jue Wang, Pedro Domingos
130
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MMSEC
2005
ACM
147views Multimedia» more  MMSEC 2005»
15 years 9 months ago
A Bayesian image steganalysis approach to estimate the embedded secret message
Image steganalysis so far has dealt only with detection of a hidden message and estimation of some of its parameters (e.g., message length and secret key). To our knowledge, so fa...
Aruna Ambalavanan, Rajarathnam Chandramouli