3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Agnostic Active Learning of Single Index Models with Linear Sample Complexity
Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu +3
We study active learning methods for single index models of the form , where and ${\mathb…
cs.LG2022
Active Learning for Single Neuron Models with Lipschitz Non-Linearities
Aarshvi Gajjar, Chinmay Hegde, Christopher Musco
We consider the problem of active learning for single neuron models, also sometimes called ``ridge functions'', in the agnostic setting (under adversarial label noise). Such models…
cs.LG2020★ 3 cited
Subspace Embeddings Under Nonlinear Transformations
Aarshvi Gajjar, Cameron Musco
We consider low-distortion embeddings for subspaces under \emph{entrywise nonlinear transformations}. In particular we seek embeddings that preserve the norm of all vectors in a sp…