37 search results - page 4 / 8 » Toward Learning Gaussian Mixtures with Arbitrary Separation |
139
Voted
ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
We consider the task of under-determined reverberant audio source separation. We model the contribution of each source to all mixture channels in the time-frequency domain as a ze...
137
Voted
UAI
2000
15 years 5 months ago
2000
In this paper we address the problem of learning the structure of a Bayesian network in domains with continuous variables. This task requires a procedure for comparing different c...
142
Voted
ICDM
2008
IEEE
15 years 10 months ago
2008
IEEE
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
151
Voted
PAMI
2008
15 years 3 months ago
2008
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
155
Voted
ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
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...