We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
For non-rigid registration, the objects in medical images are usually treated as a single deformable body with homogeneous stiffness distribution. However, this assumption is inval...
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Program dynamic optimization, adaptive to runtime behavior changes, has become increasingly important for both performance and energy savings. However, most runtime optimizations o...
Resources including various assets of supply chains, face random demand over time and can be shared by others. We consider an operational setting where a resource is shared by two...