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» Learning Mixtures of Gaussians
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TASLP
2010
138views more  TASLP 2010»
15 years 4 months ago
Source/Filter Model for Unsupervised Main Melody Extraction From Polyphonic Audio Signals
— Extracting the main melody from a polyphonic music recording seems natural even to untrained human listeners. To a certain extent it is related to the concept of source separat...
Jean-Louis Durrieu, Gaël Richard, Bertrand Da...
NIPS
2004
15 years 7 months ago
Blind One-microphone Speech Separation: A Spectral Learning Approach
We present an algorithm to perform blind, one-microphone speech separation. Our algorithm separates mixtures of speech without modeling individual speakers. Instead, we formulate ...
Francis R. Bach, Michael I. Jordan
NIPS
1998
15 years 7 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
IJON
2002
105views more  IJON 2002»
15 years 6 months ago
Separation of sources using simulated annealing and competitive learning
This paper presents a new adaptive procedure for the linear and non-linear separation of signals with non-uniform, symmetrical probability distributions, based on both simulated a...
Carlos García Puntonet, Ali Mansour, Christ...
JMLR
2010
125views more  JMLR 2010»
15 years 1 months ago
Regret Bounds for Gaussian Process Bandit Problems
Bandit algorithms are concerned with trading exploration with exploitation where a number of options are available but we can only learn their quality by experimenting with them. ...
Steffen Grünewälder, Jean-Yves Audibert,...