In this paper a holistic method and a local method based on decision template ensemble are investigated. In addition by combining both methods, a new hybrid method for boosting the...
Mohammad Sajjad Ghaemi, Saeed Masoudnia, Reza Ebra...
Seed sampling is critical in semi-supervised learning. This paper proposes a clusteringbased stratified seed sampling approach to semi-supervised learning. First, various clusteri...
To solve the knowledge bottleneck problem, active learning has been widely used for its ability to automatically select the most informative unlabeled examples for human annotation...
Jingbo Zhu, Huizhen Wang, Benjamin K. Tsou, Matthe...
Motivated by current technological advances in the design of real-time embedded systems, this work deals with the digital control of a continuous-time linear time-invariant (LTI) s...
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...