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The Ethereal
Adversarial Online Learning with noise
October 22, 2018 ยท Declared Dead ยท ๐ International Conference on Machine Learning
"No code URL or promise found in abstract"
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Authors
Alon Resler, Yishay Mansour
arXiv ID
1810.09346
Category
cs.LG: Machine Learning
Cross-listed
stat.ML
Citations
17
Venue
International Conference on Machine Learning
Last Checked
4 months ago
Abstract
We present and study models of adversarial online learning where the feedback observed by the learner is noisy, and the feedback is either full information feedback or bandit feedback. Specifically, we consider binary losses xored with the noise, which is a Bernoulli random variable. We consider both a constant noise rate and a variable noise rate. Our main results are tight regret bounds for learning with noise in the adversarial online learning model.
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