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Experiments with Random Projection
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Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures of Gausians. Here we summarize these results and illustrate them by a wide variety of experiments on synthetic and real data.
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Cited by 1 Pith paper
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Compressed Bayesian Tensor Regression
Compressed Bayesian tensor regression uses random projections to shrink tensor inputs before a low-rank Bayesian fit, reporting better out-of-sample forecasts at lower computational cost than uncompressed tensor regression.
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