Pattern Recognition and Machine Learning
Citations
126 citations
Cites methods from "Pattern Recognition and Machine Lea..."
...For each class, we train the mixture of Gaussians (5) with k = 5 using the EM algorithm [7] based on data {Nt; 0 < t ≤ 144n} from the training channels....
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126 citations
Cites background or methods from "Pattern Recognition and Machine Lea..."
...It is a highly modular software that was created based on existing theory of data analysis (Alpaydin, 2004; Bishop, 2006; Duda et al., 2001; Guyon et al., 2006; Hastie et al., 2007; Kuncheva, 2004), and as such, applied to VBS (Griffiths and Haseth, 2007; Somorjai, 2009), bringing together families…...
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...Received on December 3, 2012; revised on February 8, 2013; accepted on February 13, 2013...
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126 citations
Cites background from "Pattern Recognition and Machine Lea..."
...Generative models are very popular in the machine learning community, with many variations in existence [e.g. Roweis and Ghahramani 1999, Bishop 2006, Buxton 2003]....
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...Generative models are very popular in the machine learning community, with many variations in existence (e.g. Roweis and Ghahramani 1999; Bishop 2006; Buxton 2003)....
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126 citations
126 citations
Cites background or methods from "Pattern Recognition and Machine Lea..."
...This effect is known as overfitting [6, 7]....
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...We demonstrate in Fig 2D and 2F the improved generalization capability of this model for the learning approach Eq (2) (learning of the posterior), compared with maximum likelihood learning (approach Eq (1)), which had been theoretically predicted by [6] and [7]....
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...This new model satisfies theoretical requirements for handling priors such as structural constraints and rules in a principled manner, that have previously already been formulated and explored in the context of artificial neural networks [6, 7], as well as more recent challenges that arise from probabilistic brain models [8]....
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...Thus the learning process approximates for low values of Tmaximum a posteriori (MAP) inference [7]....
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...A thorough discussion on this topic which is known as Bayesian regularization can be found in [6, 7]....
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