We present a general approach to model selection and regularization that exploits unlabeled data to adaptively control hypothesis complexity in supervised learning tasks. The idea ...
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...
A multi-view gait recognition method using recovered static body parameters of subjects is presented; we refer to these parameters as activity-specific biometrics. Our data consis...
Abstract— This paper proposes a novel two-stage optimization method for robust Model Predictive Control (RMPC) with Gaussian disturbance and state estimation error. Since the dis...
A gait-recognition technique that recovers static body and stride parameters of subjects as they walk is presented. This approach is an example of an activity-specific biometric: ...