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» Optimizing Complex Loss Functions in Structured Prediction
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BMCBI
2007
143views more  BMCBI 2007»
14 years 9 months ago
An adaptive bin framework search method for a beta-sheet protein homopolymer model
Background: The problem of protein structure prediction consists of predicting the functional or native structure of a protein given its linear sequence of amino acids. This probl...
Alena Shmygelska, Holger H. Hoos
JMLR
2012
13 years 3 days ago
SpeedBoost: Anytime Prediction with Uniform Near-Optimality
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
Alexander Grubb, Drew Bagnell
ESWA
2007
127views more  ESWA 2007»
14 years 9 months ago
Clustering support vector machines for protein local structure prediction
Understanding the sequence-to-structure relationship is a central task in bioinformatics research. Adequate knowledge about this relationship can potentially improve accuracy for ...
Wei Zhong, Jieyue He, Robert W. Harrison, Phang C....
AI
2008
Springer
14 years 9 months ago
Label ranking by learning pairwise preferences
Preference learning is a challenging problem that involves the prediction of complex structures, such as weak or partial order relations, rather than single values. In the recent ...
Eyke Hüllermeier, Johannes Fürnkranz, We...
ICML
2009
IEEE
15 years 10 months ago
Importance weighted active learning
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
Alina Beygelzimer, Sanjoy Dasgupta, John Langford