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ACL
2012
11 years 11 months ago
A Probabilistic Model for Canonicalizing Named Entity Mentions
We present a statistical model for canonicalizing named entity mentions into a table whose rows represent entities and whose columns are attributes (or parts of attributes). The m...
Dani Yogatama, Yanchuan Sim, Noah A. Smith
BIOCOMP
2006
13 years 10 months ago
Computational Inference of Compound-induced Anti-inflammatory Effects Across Time in an Adjuvant-induced Arthritis Rat Model
A number of diseases, such as arthritis and cardiovascular disorders impacting the lives of many people have strong inflammatory components. To elucidate the antiinflammatory mecha...
Jing Yu, Gabriel Helmlinger, Muriel Saulnier, Anna...
JMLR
2010
134views more  JMLR 2010»
13 years 3 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
NIPS
1998
13 years 10 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
Bayesian Generalized Kernel Models
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...