Learning from Label Proportions: A Mutual Contamination Framework

Learning from Label Proportions: A Mutual Contamination Framework

12 June 2020

Clayton Scott

Papers citing "Learning from Label Proportions: A Mutual Contamination Framework"

7 / 7 papers shown

Title
Evaluating LLP Methods: Challenges and Approaches Gabriel Franco Giovanni V. Comarela Mark Crovella 26 0 0 29 Oct 2023
Learning under Label Proportions for Text Classification Jatin Chauhan Xiaoxuan Wang Wei Wang 33 1 0 18 Oct 2023
Label Differential Privacy via Aggregation Anand Brahmbhatt Rishi Saket Shreyas Havaldar Anshul Nasery A. Raghuveer 45 0 0 16 Oct 2023
Kernel Density Matrices for Probabilistic Deep Learning Fabio A. González Raúl Ramos-Pollán Joseph A. Gallego-Mejia 21 2 0 26 May 2023
AUC Optimization from Multiple Unlabeled Datasets Zheng Xie Yu Liu Ming Li 73 1 0 25 May 2023
Learning crop type mapping from regional label proportions in large-scale SAR and optical imagery L. E. L. Rosa Dario Augusto Borges Oliveira Pedram Ghamisi 34 8 0 24 Aug 2022
Decontamination of Mutual Contamination Models Julian Katz-Samuels Gilles Blanchard Clayton Scott 69 24 0 30 Sep 2017