Estimating the Accuracies of Multiple Classifiers Without Labeled Data

29 July 2014

Papers citing "Estimating the Accuracies of Multiple Classifiers Without Labeled Data"

9 / 9 papers shown

Title
DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples Yi Xu Jiandong Ding Lu Zhang Shuigeng Zhou 39 32 0 26 Oct 2021
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles Jiefeng Chen Frederick Liu Besim Avci Xi Wu Yingyu Liang S. Jha 32 61 0 29 Jun 2021
Seed Word Selection for Weakly-Supervised Text Classification with Unsupervised Error Estimation Yiping Jin Akshay Bhatia Dittaya Wanvarie 54 9 0 20 Apr 2021
Spectral neighbor joining for reconstruction of latent tree models Ariel Jaffe Noah Amsel Yariv Aizenbud B. Nadler Joseph T. Chang Y. Kluger BDL 11 4 0 28 Feb 2020
Limitations of Assessing Active Learning Performance at Runtime D. Kottke Jim Schellinger Denis Huseljic Bernhard Sick 20 15 0 29 Jan 2019
Agreement Rate Initialized Maximum Likelihood Estimator for Ensemble Classifier Aggregation and Its Application in Brain-Computer Interface Dongrui Wu Vernon J. Lawhern Stephen M. Gordon Brent Lance Chin-Teng Lin 9 3 0 12 May 2018
Unsupervised Ensemble Regression Omer Dror B. Nadler E. Bilal Y. Kluger 13 3 0 08 Mar 2017
Concrete Problems in AI Safety Dario Amodei C. Olah Jacob Steinhardt Paul Christiano John Schulman Dandelion Mané 24 2,319 0 21 Jun 2016
Unsupervised Ensemble Learning with Dependent Classifiers Ariel Jaffe Ethan Fetaya B. Nadler Tingting Jiang Y. Kluger UQCV 18 44 0 20 Oct 2015