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» A Generative Probabilistic OCR Model for NLP Applications
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CVPR
2010
IEEE
14 years 3 months ago
Clustering Dynamic Textures with the Hierarchical EM Algorithm
The dynamic texture (DT) is a probabilistic generative model, defined over space and time, that represents a video as the output of a linear dynamical system (LDS). The DT model ...
Antoni Chan, Emanuele Coviello, Gert Lanckriet
CORR
1998
Springer
96views Education» more  CORR 1998»
13 years 7 months ago
Similarity-Based Models of Word Cooccurrence Probabilities
Abstract. In many applications of natural language processing (NLP) it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer may ne...
Ido Dagan, Lillian Lee, Fernando C. N. Pereira
PAKDD
2005
ACM
184views Data Mining» more  PAKDD 2005»
14 years 1 months ago
Adjusting Mixture Weights of Gaussian Mixture Model via Regularized Probabilistic Latent Semantic Analysis
Mixture models, such as Gaussian Mixture Model, have been widely used in many applications for modeling data. Gaussian mixture model (GMM) assumes that data points are generated fr...
Luo Si, Rong Jin
WWW
2006
ACM
14 years 8 months ago
Probabilistic models for discovering e-communities
The increasing amount of communication between individuals in e-formats (e.g. email, Instant messaging and the Web) has motivated computational research in social network analysis...
Ding Zhou, Eren Manavoglu, Jia Li, C. Lee Giles, H...
ICDE
2009
IEEE
178views Database» more  ICDE 2009»
13 years 5 months ago
Efficient Query Evaluation over Temporally Correlated Probabilistic Streams
Many real world applications such as sensor networks and other monitoring applications naturally generate probabilistic streams that are highly correlated in both time and space. ...
Bhargav Kanagal, Amol Deshpande