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» A Preference Model for Structured Supervised Learning Tasks
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JMLR
2006
169views more  JMLR 2006»
14 years 9 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
CIKM
2011
Springer
13 years 9 months ago
Content based social behavior prediction: a multi-task learning approach
The study of information flow analyzes the principles and mechanisms of social information distribution. It is becoming an extremely important research topic in social network re...
Hongliang Fei, Ruoyi Jiang, Yuhao Yang, Bo Luo, Ju...
JMLR
2008
100views more  JMLR 2008»
14 years 9 months ago
Hit Miss Networks with Applications to Instance Selection
In supervised learning, a training set consisting of labeled instances is used by a learning algorithm for generating a model (classifier) that is subsequently employed for decidi...
Elena Marchiori
IPM
2007
149views more  IPM 2007»
14 years 9 months ago
Web page title extraction and its application
This paper is concerned with automatic extraction of titles from the bodies of HTML documents (web pages). Titles of HTML documents should be correctly defined in the title fields...
Yewei Xue, Yunhua Hu, Guomao Xin, Ruihua Song, Shu...
SSPR
2010
Springer
14 years 8 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...