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» Hedging predictions in machine learning
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ROBOCUP
2004
Springer
106views Robotics» more  ROBOCUP 2004»
15 years 11 months ago
Predicting Opponent Actions by Observation
In competitive domains, the knowledge about the opponent can give players a clear advantage. This idea lead us in the past to propose an approach to acquire models of opponents, ba...
Agapito Ledezma, Ricardo Aler, Araceli Sanch&iacut...
PPSN
2010
Springer
15 years 4 months ago
Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
BMCBI
2010
107views more  BMCBI 2010»
15 years 1 months ago
Interaction prediction and classification of PDZ domains
Background: PDZ domain is a well-conserved, structural protein domain found in hundreds of signaling proteins that are otherwise unrelated. PDZ domains can bind to the C-terminal ...
Sibel Kalyoncu, Ozlem Keskin, Attila Gürsoy
ICML
2007
IEEE
16 years 7 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
ICML
2007
IEEE
16 years 7 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann