Omer Dror — accepted AI-conference papers

2022

Crowdsourcing Regression: A Spectral Approach

Yaniv Tenzer, Omer Dror, Boaz Nadler, Erhan Bilal, Yuval Kluger

AISTATS 2022poster

Merging the predictions of multiple experts is a frequent task. When ground-truth response values are available, this merging is often based on the estimated accuracies of the experts. In various applications, however, the only available information are the experts’ predictions on unlabeled test dat…

Cited by 2 Source ↗PDF ↗Scholar ↗

2016

A Deep Learning Approach to Unsupervised Ensemble Learning

Uri Shaham, Xiuyuan Cheng, Omer Dror, Ariel Jaffe, Boaz Nadler, Joseph Chang +1

ICML 2016poster

We show how deep learning methods can be applied in the context of crowdsourcing and unsupervised ensemble learning. First, we prove that the popular model of Dawid and Skene, which assumes that all classifiers are conditionally independent, is \em equivalent to a Restricted Boltzmann Machine (RBM)…

Cited by 50 Source ↗PDF ↗code ↗Scholar ↗