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ICML
2000
IEEE
16 years 7 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»
15 years 5 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
ICML
2009
IEEE
16 years 7 months ago
Exploiting sparse Markov and covariance structure in multiresolution models
We consider Gaussian multiresolution (MR) models in which coarser, hidden variables serve to capture statistical dependencies among the finest scale variables. Tree-structured MR ...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
ICML
2004
IEEE
16 years 1 days ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi
ACL
1997
15 years 8 months ago
A Structured Language Model
A new language model for speech recognition inspired by linguistic analysis is presented. The model develops hidden hierarchical structure incrementally and uses it to extract mea...
Ciprian Chelba