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Spring 2019
In this thesis we introduce a new loss for regression, the Histogram Loss. There is some evidence that, in the problem of sequential decision making, estimating the full distribution of return offers a considerable gain in performance, even though only the mean of that distribution is used in...
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Fall 2024
Classical wisdom in machine learning advises controlling the complexity of the hypothesis space for achieving good generalization. Despite this, modern overparametrized neural networks demonstrate remarkably high generalization performance, oftentimes with larger and more expressive architectures...