Machine Learning · Computer Science
To Each Optimizer a Norm, To Each Norm its Generalization
Sharan Vaswani, Reza Babanezhad, Jose Gallego-Posada, Aaron Mishkin +2
2022-07-12
Machine Learning · Statistics
Interpolation and Learning with Scale Dependent Kernels
Nicolò Pagliana, Alessandro Rudi, Ernesto De Vito, Lorenzo Rosasco
2021-11-11
Machine Learning · Statistics
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy
Alex Lamb, Vikas Verma, Kenji Kawaguchi, Alexander Matyasko +3
2022-10-20
Machine Learning · Computer Science
A Class of Geometric Structures in Transfer Learning: Minimax Bounds and Optimality
Xuhui Zhang, Jose Blanchet, Soumyadip Ghosh, Mark S. Squillante
2022-02-24
Machine Learning · Statistics
Regularization properties of adversarially-trained linear regression
Antônio H. Ribeiro, Dave Zachariah, Francis Bach, Thomas B. Schön
2023-10-18
Statistics Theory · Mathematics
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Trevor Hastie, Andrea Montanari, Saharon Rosset, Ryan J. Tibshirani
2022-09-12
Machine Learning · Statistics
Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression
Lijia Zhou, Frederic Koehler, Danica J. Sutherland, Nathan Srebro
2021-12-09
Numerical Analysis · Mathematics
Efficient learning methods for large-scale optimal inversion design
Julianne Chung, Matthias Chung, Silvia Gazzola, Mirjeta Pasha
2021-10-07
Machine Learning · Computer Science
On the Implicit Bias of Gradient Descent for Temporal Extrapolation
Edo Cohen-Karlik, Avichai Ben David, Nadav Cohen, Amir Globerson
2022-03-25