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ECML
2007
Springer
15 years 3 months ago
Source Separation with Gaussian Process Models
In this paper we address a method of source separation in the case where sources have certain temporal structures. The key contribution in this paper is to incorporate Gaussian pro...
Sunho Park, Seungjin Choi
KDD
2008
ACM
257views Data Mining» more  KDD 2008»
15 years 10 months ago
Knowledge discovery of semantic relationships between words using nonparametric bayesian graph model
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
Issei Sato, Minoru Yoshida, Hiroshi Nakagawa
ICA
2010
Springer
14 years 10 months ago
Use of Prior Knowledge in a Non-Gaussian Method for Learning Linear Structural Equation Models
Abstract. We discuss causal structure learning based on linear structural equation models. Conventional learning methods most often assume Gaussianity and create many indistinguish...
Takanori Inazumi, Shohei Shimizu, Takashi Washio
ICASSP
2011
IEEE
14 years 1 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...
EGITALY
2006
14 years 11 months ago
3D Data Segmentation Using a Non-Parametric Density Estimation Approach
In this paper, a new segmentation approach for sets of 3D unorganized points is proposed. The method is based on a clustering procedure that separates the modes of a non-parametri...
Umberto Castellani, Marco Cristani, Vittorio Murin...