SENTRY: Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation-Reference-Cited by-同舟云学术

SENTRY: Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation

Published:2021-10 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Prabhu Viraj¹,Khare Shivam¹,Kartik Deeksha¹,Hoffman Judy¹

Affiliation:

1. Georgia Institute of Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9709627/9709628/09710018.pdf?arnumber=9710018

Reference55 articles.

1. Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift;snoek;Advances in neural information processing systems,2019

2. Regularization with stochastic transformations and perturbations for deep semi-supervised learning;sajjadi,2016

3. Regularizing neural networks by penalizing confident output distributions;pereyra;ICLRE,2017

4. Visda: The visual domain adaptation challenge;peng,2017

5. Moment Matching for Multi-Source Domain Adaptation

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