—We review the principles of Minimum Description Length and Stochastic Complexity as used in data compression and statistical modeling. Stochastic complexity is formulated as the...
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Active shape models are a powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowle...
Groupwise non-rigid registration aims to find a dense correspondence across a set of images, so that analogous structures in the images are aligned. For purely automatic inter-sub...
Stephen Marsland, Carole J. Twining, Christopher J...