10 citations · 12 across the 2 of their papers we have counts for
3 papers
cs.LG2024
Computational-Statistical Gaps in Gaussian Single-Index Models
Alex Damian, Loucas Pillaud-Vivien, Jason D. Lee +1
Single-Index Models are high-dimensional regression problems with planted structure, whereby labels depend on an unknown one-dimensional projection of the input via a generic, non-…
cs.LG2023★ 2 cited
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models
Alex Damian, Eshaan Nichani, Rong Ge +1
We focus on the task of learning a single index model with respect to the isotropic Gaussian distribution in dimensions. Prior work has shown that the samp…
cs.LG2022★ 10 cited
Neural Networks can Learn Representations with Gradient Descent
Alex Damian, Jason D. Lee, Mahdi Soltanolkotabi
Significant theoretical work has established that in specific regimes, neural networks trained by gradient descent behave like kernel methods. However, in practice, it is known tha…