3 papers
cs.LG2025
A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
Gil Goldshlager, Jiang Hu, Lin Lin
Subsampled natural gradient descent (SNG) has been used to enable high-precision scientific machine learning, but standard analyses based on stochastic preconditioning fail to prov…
cs.LG2025
Worth Their Weight: Randomized and Regularized Block Kaczmarz Algorithms without Preprocessing
Gil Goldshlager, Jiang Hu, Lin Lin
Due to the ever growing amounts of data leveraged for machine learning and scientific computing, it is increasingly important to develop algorithms that sample only a small portion…
physics.comp-ph2024
A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions
Gil Goldshlager, Nilin Abrahamsen, Lin Lin
Neural network wavefunctions optimized using the variational Monte Carlo method have been shown to produce highly accurate results for the electronic structure of atoms and small m…