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cs.LG2023★ 1 cited
Sample Complexity Bounds for Estimating Probability Divergences under Invariances
Behrooz Tahmasebi, Stefanie Jegelka
Group-invariant probability distributions appear in many data-generative models in machine learning, such as graphs, point clouds, and images. In practice, one often needs to estim…
cs.LG2023★ 3 cited
The Exact Sample Complexity Gain from Invariances for Kernel Regression
Behrooz Tahmasebi, Stefanie Jegelka
In practice, encoding invariances into models improves sample complexity. In this work, we study this phenomenon from a theoretical perspective. In particular, we provide minimax o…