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COLT
2005
Springer
14 years 2 months ago
Ranking and Scoring Using Empirical Risk Minimization
A general model is proposed for studying ranking problems. We investigate learning methods based on empirical minimization of the natural estimates of the ranking risk. The empiric...
Stéphan Clémençon, Gáb...
NIPS
2007
13 years 10 months ago
A Risk Minimization Principle for a Class of Parzen Estimators
This paper1 explores the use of a Maximal Average Margin (MAM) optimality principle for the design of learning algorithms. It is shown that the application of this risk minimizati...
Kristiaan Pelckmans, Johan A. K. Suykens, Bart De ...
EMNLP
2006
13 years 10 months ago
Automatic Construction of Predicate-argument Structure Patterns for Biomedical Information Extraction
This paper presents a method of automatically constructing information extraction patterns on predicate-argument structures (PASs) obtained by full parsing from a smaller training...
Akane Yakushiji, Yusuke Miyao, Tomoko Ohta, Yuka T...
IJCNN
2006
IEEE
14 years 3 months ago
Sparse Bayesian Models: Bankruptcy-Predictors of Choice?
Abstract— Making inferences and choosing appropriate responses based on incomplete, uncertainty and noisy data is challenging in financial settings particularly in bankruptcy de...
Bernardete Ribeiro, Armando Vieira, João Ca...
ICML
2006
IEEE
14 years 10 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...