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ICMLA
2008
13 years 9 months ago
A Clustering Approach in Developing Prognostic Systems of Cancer Patients
Accurate prediction of survival rates of cancer patients is often key to stratify patients for prognosis and treatment. Survival prediction is often accomplished by the TNM system...
Dechang Chen, Kai Xing, Donald Henson, Li Sheng, A...
ICML
2006
IEEE
14 years 8 months ago
A graphical model for predicting protein molecular function
We present a simple statistical model of molecular function evolution to predict protein function. The model description encodes general knowledge of how molecular function evolve...
Barbara E. Engelhardt, Michael I. Jordan, Steven E...
CVPR
2009
IEEE
15 years 2 months ago
Learning Based Automatic Face Annotation for Arbitrary Poses and Expressions from Frontal Images Only
Statistical approaches for building non-rigid deformable models, such as the Active Appearance Model (AAM), have enjoyed great popularity in recent years, but typically require ...
Akshay Asthana (Australian National University), R...
ICS
2005
Tsinghua U.
14 years 1 months ago
What is worth learning from parallel workloads?: a user and session based analysis
Learning useful and predictable features from past workloads and exploiting them well is a major source of improvement in many operating system problems. We review known parallel ...
Julia Zilber, Ofer Amit, David Talby
COLT
1999
Springer
14 years 1 hour ago
Regret Bounds for Prediction Problems
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
Geoffrey J. Gordon