2 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 1 cited
Aiming towards the minimizers: fast convergence of SGD for overparametrized problems
Chaoyue Liu, Dmitriy Drusvyatskiy, Mikhail Belkin +2
Modern machine learning paradigms, such as deep learning, occur in or close to the interpolation regime, wherein the number of model parameters is much larger than the number of da…
cs.LG2023★ 2 cited
Disentangled Multi-Fidelity Deep Bayesian Active Learning
Dongxia Wu, Ruijia Niu, Matteo Chinazzi +2
To balance quality and cost, various domain areas of science and engineering run simulations at multiple levels of sophistication. Multi-fidelity active learning aims to learn a di…