Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization
نویسندگان
چکیده
منابع مشابه
Conditional Density Estimation with Dimensionality Reduction via Squared-Loss Conditional Entropy Minimization
Regression aims at estimating the conditional mean of output given input. However, regression is not informative enough if the conditional density is multimodal, heteroskedastic, and asymmetric. In such a case, estimating the conditional density itself is preferable, but conditional density estimation (CDE) is challenging in high-dimensional space. A naive approach to coping with high dimension...
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Reducing the dimensionality of high-dimensional data without losing its essential information is an important task in information processing. When class labels of training data are available, Fisher discriminant analysis (FDA) has been widely used. However, the optimality of FDA is guaranteed only in a very restricted ideal circumstance, and it is often observed that FDA does not provide a good...
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ژورنال
عنوان ژورنال: Neural Computation
سال: 2015
ISSN: 0899-7667,1530-888X
DOI: 10.1162/neco_a_00683