While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
In this paper, we propose a novel approach to model shape variations. It encodes sparsity, exploits geometric redundancy, and accounts for the different degrees of local variation...
— A fundamental problem in the field of motor neuroscience is to understand how our brain generates appropriate motor commands for precise movements effortlessly. The problem se...
This work proposes and evaluates improvements to previously known algorithms for redundancy elimination. Enhanced Scalar Replacement combines two classic techniques, scalar replac...
This work attempts to considerably reduce the amount of user effort in the natural image matting problem. The key observation is that the nonlocal principle, introduced to denoise...