One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
In this paper, we consider representing a musical signal as a dynamic texture, a model for both the timbral and rhythmical qualities of sound. We apply the new representation to t...
Luke Barrington, Antoni B. Chan, Gert R. G. Lanckr...
—This paper addresses the issue of matching rigid and articulated shapes through probabilistic point registration. The problem is recast into a missing data framework where unkno...
Radu Horaud, Florence Forbes, Manuel Yguel, Guilla...
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
— We investigate the throughput improvement that ZIGZAG decoding (Gollakota and Katabi (2008)) can achieve in multi-user random access systems. ZIGZAG is a recently proposed 802....