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» The Infinite Hidden Markov Model
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ICML
2005
IEEE
15 years 12 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 ...
ICML
2000
IEEE
15 years 12 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...
TKDE
2010
150views more  TKDE 2010»
14 years 9 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
MMSEC
2005
ACM
147views Multimedia» more  MMSEC 2005»
15 years 4 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
ECML
2004
Springer
15 years 4 months ago
Fisher Kernels for Logical Sequences
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...
Kristian Kersting, Thomas Gärtner