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» A Preference Model for Structured Supervised Learning Tasks
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AUSAI
2008
Springer
14 years 11 months ago
Learning a Generative Model for Structural Representations
Abstract. Graph-based representations have been used with considercess in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the ...
Andrea Torsello, David L. Dowe
SDM
2009
SIAM
162views Data Mining» more  SDM 2009»
15 years 6 months ago
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction.
We propose Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using aux...
Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanish...
84
Voted
CORR
2002
Springer
142views Education» more  CORR 2002»
14 years 9 months ago
Learning Algorithms for Keyphrase Extraction
Many academic journals ask their authors to provide a list of about five to fifteen keywords, to appear on the first page of each article. Since these key words are often phrases ...
Peter D. Turney
87
Voted
ICASSP
2011
IEEE
14 years 1 months ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
ICASSP
2011
IEEE
14 years 1 months ago
Maximum margin structure learning of Bayesian network classifiers
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
Franz Pernkop, Michael Wohlmay, Manfred Mücke