How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget

6 June 2023

Papers citing "How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget"

10 / 10 papers shown

Title
Active Learning with a Noisy Annotator Netta Shafir Guy Hacohen D. Weinshall 28 0 0 06 Apr 2025
Bridging Diversity and Uncertainty in Active learning with Self-Supervised Pre-Training Paul Doucet Benjamin Estermann Till Aczél Roger Wattenhofer 141 4 0 20 Jan 2025
Uncertainty Herding: One Active Learning Method for All Label Budgets Wonho Bae Gabriel L. Oliveira Danica J. Sutherland UQCV 80 0 0 30 Dec 2024
AutoAL: Automated Active Learning with Differentiable Query Strategy Search Yifeng Wang Xueying Zhan Siyu Huang OOD 27 0 0 17 Oct 2024
Generalized Coverage for More Robust Low-Budget Active Learning Wonho Bae Junhyug Noh Danica J. Sutherland 22 3 0 16 Jul 2024
DCoM: Active Learning for All Learners Inbal Mishal D. Weinshall VLM 20 0 0 01 Jul 2024
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification Denis Huseljic Paul Hahn M. Herde Lukas Rauch Bernhard Sick 18 1 0 13 Apr 2024
Optimizing Data Collection for Machine Learning Rafid Mahmood James Lucas J. Álvarez Sanja Fidler M. Law 52 26 0 03 Oct 2022
Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets Guy Hacohen Avihu Dekel D. Weinshall 119 116 0 06 Feb 2022
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 295 5,761 0 29 Apr 2021