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cs.LG2025
Regularization can make diffusion models more efficient
Mahsa Taheri, Johannes Lederer
Diffusion models are one of the key architectures of generative AI. Their main drawback, however, is the computational costs. This study indicates that the concept of sparsity, wel…
cs.LG2022
Statistical Guarantees for Approximate Stationary Points of Shallow Neural Networks
Mahsa Taheri, Fang Xie, Johannes Lederer
Since statistical guarantees for neural networks are usually restricted to global optima of intricate objective functions, it is unclear whether these theories explain the performa…
cs.LG2020
Statistical Guarantees for Regularized Neural Networks
Mahsa Taheri, Fang Xie, Johannes Lederer
Neural networks have become standard tools in the analysis of data, but they lack comprehensive mathematical theories. For example, there are very few statistical guarantees for le…