1 citations · 1 across the 6 of their papers we have counts for
8 papers
Learning Decision-Stump Thresholds in Context: Dynamics of Softmax Attention
Hong Ha Le, Jackie Lok, Atsushi Nitanda +1
Estimating a decision threshold requires locating observations near an unknown boundary. We study how gradient-based pretraining learns this statistical rule in a two-parameter sof…
Linear Systems and Eigenvalue Problems: Open Questions from a Simons Workshop
Noah Amsel, Yves Baumann, Paul Beckman +33
This document presents a series of open questions arising in matrix computations, i.e., the numerical solution of linear algebra problems. It is a result of working groups at the w…
Beyond Expectation: Concentration Inequalities for Randomized Iterative Methods
Toby Anderson, Max Collins, Jamie Haddock +2
Stochastic iterative methods are useful in a variety of large-scale numerical linear algebraic, machine learning, and statistical problems, in part due to their low-memory footprin…
Subspace-constrained randomized coordinate descent for linear systems with good low-rank matrix approximations
Jackie Lok, Elizaveta Rebrova
The randomized coordinate descent (RCD) method is a classical algorithm with simple, lightweight iterations that is widely used for various optimization problems, including the sol…
On Regularization via Early Stopping for Least Squares Regression
Rishi Sonthalia, Jackie Lok, Elizaveta Rebrova
A fundamental problem in machine learning is understanding the effect of early stopping on the parameters obtained and the generalization capabilities of the model. Even for linear…
Error dynamics of mini-batch gradient descent with random reshuffling for least squares regression
Jackie Lok, Rishi Sonthalia, Elizaveta Rebrova
We study the discrete dynamics of mini-batch gradient descent with random reshuffling for least squares regression. We show that the training and generalization errors depend on a…
On Approximating the Potts Model with Contracting Glauber Dynamics
Roxanne He, Jackie Lok
We show that the Potts model on a graph can be approximated by a sequence of independent and identically distributed spins in terms of Wasserstein distance at high temperatures. We…
A subspace constrained randomized Kaczmarz method for structure or external knowledge exploitation
Jackie Lok, Elizaveta Rebrova
We study a version of the randomized Kaczmarz algorithm for solving systems of linear equations where the iterates are confined to the solution space of a selected subsystem. We sh…