3 papers
math.NA2026
Stochastic Gradient Descent for Incomplete Tensor Linear Systems
Anna Ma, Deanna Needell, Alexander Xue
Solving large tensor linear systems poses significant challenges due to the high volume of data stored, and it only becomes more challenging when some of the data is missing. Recen…
math.NA2026
Numerical Instabilities in the Kaczmarz Method and Stabilization by Iterative Refinement
MichaÅ DereziÅski, Ethan N. Epperly, Deanna Needell +1
The randomized Kaczmarz method and its accelerated variants are a powerful class of iterative methods for solving large-scale linear systems, offering guaranteed convergence with l…
cs.LG2025
Differentially Private Random Feature Model
Chunyang Liao, Deanna Needell, Hayden Schaeffer +1
Designing privacy-preserving machine learning algorithms has received great attention in recent years, especially in the setting when the data contains sensitive information. Diffe…