Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
This paper proposes a dereverberation method for musical audio signals. Existing dereverberation methods are designed for speech signals and are not necessarily effective for supp...
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
This paper presents a new wavelet based retrieval approach based on Spherically Invariant Random Vector (SIRV) modeling of wavelet subbands. Under this multivariate model, wavelet...
We consider single-stage, single-product Make-to-Stock systems with random demand and random service (production) rate, where demand shortages at the inventory facility are backor...