A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity

8 April 2021

Papers citing "A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity"

8 / 8 papers shown

Title
Feasibility Study on Active Learning of Smart Surrogates for Scientific Simulations Pradeep Bajracharya J. Q. Toledo-Marín Geoffrey C. Fox S. Jha Linwei Wang AI4CE 45 1 0 10 Jul 2024
BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges Hoyong Choi Nohyun Ki Hye Won Chung 29 2 0 05 Jun 2024
NTKCPL: Active Learning on Top of Self-Supervised Model by Estimating True Coverage Ziting Wen Oscar Pizarro Stefan B. Williams 19 2 0 07 Jun 2023
Active Semi-Supervised Learning by Exploring Per-Sample Uncertainty and Consistency Jae-Kwang Lim Jongkeun Na Nojun Kwak 40 1 0 15 Mar 2023
Continuous Learning for Android Malware Detection Yizheng Chen Zhoujie Ding David A. Wagner 29 32 0 08 Feb 2023
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar C. Pehlevan 144 201 0 07 Feb 2020
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 199 243 0 14 Jun 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015