3 papers
cs.LG2025
Improving Energy Natural Gradient Descent through Woodbury, Momentum, and Randomization
Andrés Guzmán-Cordero, Felix Dangel, Gil Goldshlager +1
Natural gradient methods significantly accelerate the training of Physics-Informed Neural Networks (PINNs), but are often prohibitively costly. We introduce a suite of techniques t…
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…
math.NA2024
Randomized Kaczmarz with tail averaging
Ethan N. Epperly, Gil Goldshlager, Robert J. Webber
The randomized Kaczmarz (RK) method is a well-known approach for solving linear least-squares problems with a large number of rows. RK accesses and processes just one row at a time…