We introduce in this paper the family of information-based models for ad hoc information retrieval. These models draw their inspiration from a long-standing hypothesis in IR, name...
This paper proposes an interpolating extension to hidden Markov models (HMMs), which allows more accurate modeling of natural sounds sources. The model is able to produce observat...
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...
—We propose a statistical framework for high-level feature extraction that uses SIFT Gaussian mixture models (GMMs) and audio models. SIFT features were extracted from all the im...
We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...