It is well-known that scale space theory and Tikhonov regularization are close-knit. In previous studies qualitative analogies and formal relations had already been found, but non...
This report develops and studies a new family of NSE-regularizations, Tikhonov Leray Regularization with Time Relaxation Models. This new family of turbulence models is based on a...
Abstract. Regularization o ers a powerful framework for signal reconstruction by enforcing weak constraints through the use of stabilizers. Stabilizers are functionals measuring th...
We consider symbolic dynamic programming (SDP) for solving Markov Decision Processes (MDP) with factored state and action spaces, where both states and actions are described by se...
Aswin Raghavan, Saket Joshi, Alan Fern, Prasad Tad...
We are motivated by a recently developed nonlinear inverse scale space method for image denoising [5, 6], whereby noise can be removed with minimal degradation. The additive noise ...