A central object of study in the field of algorithmic randomness are notions of randomness for sequences, i.e., infinite sequences of zeros and ones. These notions are usually def...
In this paper, we present an automated, quantitative, knowledge-poor method to evaluate the randomness of a collection of documents (corpus), with respect to a number of biased pa...
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
— Non-rigid object detection is a challenging open research problem in computer vision. It is a critical part in many applications such as image search, surveillance, humancomput...
Gemma Roig, Xavier Boix Bosch, Fernando De la Torr...
Abstract--In this paper, we propose a maximum-entropy expectation-maximization (MEEM) algorithm. We use the proposed algorithm for density estimation. The maximum-entropy constrain...