Active Learning for Single Neuron Models with Lipschitz Non-Linearities

24 October 2022

Papers citing "Active Learning for Single Neuron Models with Lipschitz Non-Linearities"

10 / 10 papers shown

Title
Near-Polynomially Competitive Active Logistic Regression Yihan Zhou Eric Price Trung Nguyen 46 0 0 07 Mar 2025
Near-optimal Active Regression of Single-Index Models Yi Li Wai Ming Tai 49 0 0 25 Feb 2025
Provably Accurate Shapley Value Estimation via Leverage Score Sampling Christopher Musco R. Teal Witter FAtt FedML TDI 49 2 0 02 Oct 2024
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models Sheng-Jun Huang Yi Li Yiming Sun Ying-Peng Tang 24 2 0 23 May 2024
Agnostic Active Learning of Single Index Models with Linear Sample Complexity Aarshvi Gajjar Wai Ming Tai Xingyu Xu Chinmay Hegde Yi Li Chris Musco 43 6 0 15 May 2024
A unified framework for learning with nonlinear model classes from arbitrary linear samples Ben Adcock Juan M. Cardenas N. Dexter 31 3 0 25 Nov 2023
Improved Active Learning via Dependent Leverage Score Sampling Atsushi Shimizu Xiaoou Cheng Chris Musco Jonathan Weare FedML 11 5 0 08 Oct 2023
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions Ben Adcock Juan M. Cardenas N. Dexter 24 6 0 01 Jun 2023
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 34 29 0 11 Dec 2020
$Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $ \ell^1 $ and $ \ell^0 $ Controls$ Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $\ell^1$ and $\ell^0$ Controls Jason M. Klusowski Andrew R. Barron 124 142 0 26 Jul 2016