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» Modeling Classification and Inference Learning
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COLING
2008
13 years 8 months ago
Exact Inference for Multi-label Classification using Sparse Graphical Models
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Yusuke Miyao, Jun-ichi Tsujii
ICML
2009
IEEE
14 years 7 months ago
Archipelago: nonparametric Bayesian semi-supervised learning
Semi-supervised learning (SSL), is classification where additional unlabeled data can be used to improve accuracy. Generative approaches are appealing in this situation, as a mode...
Ryan Prescott Adams, Zoubin Ghahramani
ICML
2003
IEEE
14 years 7 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
EMNLP
2008
13 years 8 months ago
Modeling Annotators: A Generative Approach to Learning from Annotator Rationales
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
Omar Zaidan, Jason Eisner
KDD
2008
ACM
174views Data Mining» more  KDD 2008»
14 years 7 months ago
Effective label acquisition for collective classification
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Mustafa Bilgic, Lise Getoor