How does unlabeled data improve generalization in self-training? A
one-hidden-layer theoretical analysis

How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis

21 January 2022

Shuai Zhang

Jinjun Xiong

Papers citing "How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis"

7 / 7 papers shown

Title
Retraining with Predicted Hard Labels Provably Increases Model Accuracy Rudrajit Das Inderjit S Dhillon Alessandro Epasto Adel Javanmard Jieming Mao Vahab Mirrokni Sujay Sanghavi Peilin Zhong 46 1 0 17 Jun 2024
$How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance$ How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance Hongkang Li Shuai Zhang Yihua Zhang Meng Wang Sijia Liu Pin-Yu Chen 33 4 0 12 Mar 2024
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption Vasilii Feofanov Malik Tiomoko Aladin Virmaux 31 5 0 20 Oct 2023
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning Jungtaek Kim 32 1 0 24 May 2023
DuNST: Dual Noisy Self Training for Semi-Supervised Controllable Text Generation Yuxi Feng Xiaoyuan Yi Xiting Wang L. Lakshmanan Xing Xie DiffM 27 5 0 16 Dec 2022
Self-Training: A Survey Massih-Reza Amini Vasilii Feofanov Loïc Pauletto Lies Hadjadj Emilie Devijver Yury Maximov SSL 26 100 0 24 Feb 2022
Revisiting Self-Training for Neural Sequence Generation Junxian He Jiatao Gu Jiajun Shen MarcÁurelio Ranzato SSL LRM 242 269 0 30 Sep 2019