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» An Introduction to Learning Structured Information
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SSPR
2004
Springer
15 years 3 months ago
Learning from General Label Constraints
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
Tijl De Bie, Johan A. K. Suykens, Bart De Moor
ML
2010
ACM
151views Machine Learning» more  ML 2010»
14 years 8 months ago
Inductive transfer for learning Bayesian networks
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
ACE
2003
86views Education» more  ACE 2003»
14 years 11 months ago
A New Approach to a First Year Undergraduate Information Systems Course
This paper describes the development, implementation and evaluation of a new teaching approach for a large first year undergraduate course in information systems at the University...
Denise Tolhurst, Bob Baker
SIGMOD
2007
ACM
125views Database» more  SIGMOD 2007»
15 years 10 months ago
Identifying meaningful return information for XML keyword search
Keyword search enables web users to easily access XML data without the need to learn a structured query language and to study possibly complex data schemas. Existing work has addr...
Ziyang Liu, Yi Chen
JMLR
2010
155views more  JMLR 2010»
14 years 4 months ago
Structured Sparse Principal Component Analysis
We present an extension of sparse PCA, or sparse dictionary learning, where the sparsity patterns of all dictionary elements are structured and constrained to belong to a prespeci...
Rodolphe Jenatton, Guillaume Obozinski, Francis Ba...