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ICASSP
2011
IEEE
13 years 1 months ago
Application specific loss minimization using gradient boosting
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
AI
2001
Springer
14 years 1 months ago
Learning about Constraints by Reflection
A system's constraints characterizes what that system can do. However, a dynamic environment may require that a system alter its constraints. If feedback about a specific situ...
J. William Murdock, Ashok K. Goel
ACL
2009
13 years 8 months ago
Learning with Annotation Noise
It is usually assumed that the kind of noise existing in annotated data is random classification noise. Yet there is evidence that differences between annotators are not always ra...
Eyal Beigman, Beata Beigman Klebanov
SMC
2007
IEEE
130views Control Systems» more  SMC 2007»
14 years 4 months ago
Simulation framework for training chest tube insertion using virtual reality and force feedback
—Most virtual reality simulators are designed for complex medical procedures, such as laparoscopic surgery. While important, these simulators are of use for only a subset of spec...
Nader S. Raja, John A. Schleser, William P. Norman...
ICML
2003
IEEE
14 years 3 months ago
Decision Tree with Better Ranking
AUC(Area Under the Curve) of ROC(Receiver Operating Characteristics) has been recently used as a measure for ranking performanceof learning algorithms. In this paper, wepresent a ...
Charles X. Ling, Robert J. Yan