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ICASSP
2010
IEEE
13 years 7 months ago
Power law discounting for n-gram language models
We present an approximation to the Bayesian hierarchical PitmanYor process language model which maintains the power law distribution over word tokens, while not requiring a comput...
Songfang Huang, Steve Renals
SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
13 years 8 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
VLDB
1998
ACM
147views Database» more  VLDB 1998»
13 years 11 months ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...
COGSCI
2008
74views more  COGSCI 2008»
13 years 7 months ago
Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds?
Griffiths and Tenenbaum (2006) asked individuals to make predictions about the duration or extent of everyday events (e.g., cake baking times), and reported that predictions were ...
Michael C. Mozer, Harold Pashler, Hadjar Homaei
IPMI
2009
Springer
14 years 8 months ago
Estimating Uncertainty in Brain Region Delineations
This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...