Zachary Frangella

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 10

Top Topics

Optimization Method

Ridge Regression

Top Venues

SIAM J. Matrix Anal. Appl.

Publications

Pratik Rathore, Weimu Lei, Zachary Frangella, Lu Lu, Madeleine Udell
Challenges in Training PINNs: A Loss Landscape Perspective. CoRR (2024)
Pratik Rathore, Zachary Frangella, Madeleine Udell
Have ASkotch: Fast Methods for Large-scale, Memory-constrained Kernel Ridge Regression. CoRR (2024)
Zachary Frangella, Joel A. Tropp, Madeleine Udell
Randomized Nyström Preconditioning. SIAM J. Matrix Anal. Appl. 44 (2) (2023)
Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber
Robust, randomized preconditioning for kernel ridge regression. CoRR (2023)
Zachary Frangella, Pratik Rathore, Shipu Zhao, Madeleine Udell
PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates. CoRR (2023)
Shipu Zhao, Zachary Frangella, Madeleine Udell
NysADMM: faster composite convex optimization via low-rank approximation. ICML (2022)
Zachary Frangella, Pratik Rathore, Shipu Zhao, Madeleine Udell
SketchySGD: Reliable Stochastic Optimization via Robust Curvature Estimates. CoRR (2022)
William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression. CoRR (2021)
Zachary Frangella, Joel A. Tropp, Madeleine Udell
Randomized Nyström Preconditioning. CoRR (2021)
William T. Stephenson, Zachary Frangella, Madeleine Udell, Tamara Broderick
Can we globally optimize cross-validation loss? Quasiconvexity in ridge regression. NeurIPS (2021)