1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Empirical Perturbation Analysis of Linear System Solvers from a Data Poisoning Perspective
Yixin Liu, Arielle Carr, Lichao Sun
The perturbation analysis of linear solvers applied to systems arising broadly in machine learning settings -- for instance, when using linear regression models -- establishes an i…
cs.LG2024
A Dynamic Weighting Strategy to Mitigate Worker Node Failure in Distributed Deep Learning
Yuesheng Xu, Arielle Carr
The increasing complexity of deep learning models and the demand for processing vast amounts of data make the utilization of large-scale distributed systems for efficient training…
cs.LG2024★ 1 cited
Deep Learning for Koopman Operator Estimation in Idealized Atmospheric Dynamics
David Millard, Arielle Carr, Stéphane Gaudreault
Deep learning is revolutionizing weather forecasting, with new data-driven models achieving accuracy on par with operational physical models for medium-term predictions. However, t…