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Showing 1 to 5 of 5 for “"Rademacher Complexity"”.
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Chain rules for Rademacher complexity
… can be considered as a control over empirical Rademacher complexity of a composite function class. Such an estimate can be applied to learning problems where the hypotheses have composite structure or where more than one function is needed to determine the empirical loss.
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Empirical Bayes via ERM and Rademacher complexities: the Poisson model
… issues, but are computationally expensive with complexity growing exponentially with dimension. Extending the approach of Barbehenn and Zhao (2022), in this work we construct monotone estimators based on empirical risk minimization (ERM) that retain similar theoretical guarantees and can be …
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Essays on Algorithmic Learning and Uncertainty Quantification
… new analytical tools based upon the offset Rademacher complexity for studying stochastic optimization in non-convex domains, including statistical prediction and model aggregation problems. Using these tools, I show that a simple procedure called the star algorithm can recover near-optimal …
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Online and active learning of big networks: theory and algorithms
… (LLGC). I show that the empirical transductive Rademacher complexity of the function class for LLGC provides a natural criterion for active learning. The resulting active learning approach is to select a subset of nodes on a graph such that the empirical transductive Rademacher complexity of …
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Nonlinear and geometric control methods in deep learning theory
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-12-01