Global ETD Search
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Showing 1 to 3 of 3 for “"Sparse mixture"”.
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Detection of sparse mixtures: fundamental limits and algorithms
In this thesis, we study the sparse mixture detection problem as a binary hypothesis testing problem. Under the null hypothesis, we observe i.i.d. samples from a known noise distribution. Under the alternative hypothesis, we observe i.i.d. samples from a mixture of the noise distribution and signal …
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Improving Deep Learning with Probabilistic Approaches
… we investigate uncertainty estimation in sparse Mixture-of-Experts models. These models learn multiple diverse explanations of the data. We show that averaging these explanations results in robust predictions with well-calibrated uncertainty estimates. We provide an algorithm for doing so …
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Nonparametric High-dimensional Models: Sparsity, Efficiency, Interpretability
… methods: additive models, tree ensembles, and mixtures of experts. Each ensemble method is characterized by a specific structure: additive models can involve base learners with single or pairwise covariates, tree ensembles use a decision tree as a base learner, and mixtures of experts typically …