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JMLR
2006
105views more  JMLR 2006»
15 years 6 months ago
Linear State-Space Models for Blind Source Separation
We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation a...
Rasmus Kongsgaard Olsson, Lars Kai Hansen
ICPR
2000
IEEE
16 years 7 months ago
A Markov Random Field Model for Automatic Speech Recognition
Speech can be represented as a time/frequency distribution of energy using a multi-band filter bank. A Markov random field model, which takes into account the possible time asynch...
Gérard Chollet, Guillaume Gravier, Marc Sig...
HICSS
2009
IEEE
147views Biometrics» more  HICSS 2009»
16 years 1 months ago
Determining a Firm's Optimal Outsourcing Rate: A Learning Model Perspective
We present a decision model of a firm’s optimal outsourcing rate as an extension of Cha et. al [1]’s previous work on the economic risk of knowledge loss and deskilling in the...
Hoon S. Cha, David E. Pingry, Matt E. Thatcher
ECSQARU
2009
Springer
16 years 1 months ago
The Probabilistic Interpretation of Model-Based Diagnosis
Model-based diagnosis is the field of research concerned with the problem of finding faults ms by reasoning with abstract models of the systems. Typically, such models offer a ...
Ildikó Flesch, Peter J. F. Lucas
CIRA
2007
IEEE
179views Robotics» more  CIRA 2007»
16 years 28 days ago
Learning Tactic-Based Motion Models of a Moving Object with Particle Filtering
— Learning motion models of a moving object is a challenge for autonomous robots. We address the particular instance of parameter learning when tracking object motions in a switc...
Yang Gu, Manuela M. Veloso