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The Predictive Normalized Maximum Likelihood (pNML) scheme has been recently suggested for universal learning in the individual setting, where both the training and test samples are individual data.
A theory of the learnable
Leslie G Valiant · 1984
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Universal sequential coding of single messages
Yurii Mikhailovich Shtarkov · 1987
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Principles of risk minimization for learning theory
Vladimir Vapnik · 1992
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MNIST handwritten digit database
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Reading digits in natural images with unsupervised feature learning
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Elements of information theory
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Enhancing the reliability of out-of-distribution image detection in neural networks
Shiyu Liang, Yixuan Li, and R Srikant · 2017
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Towards deep learning models resistant to adversarial attacks
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Dan Hendrycks and Kevin Gimpel · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Universal Batch Learning with Log-loss in the Individual Setting
Yaniv Fogel and Meir Feder
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Universal Supervised Learning for Individual Data
Yaniv Fogel and Meir Feder
Cited in the paper.
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Confidence prediction for lexicon-free ocr
Noam Mor and Lior Wolf · 2018
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New look at an old problem: A universal learning approach to linear regression
Koby Bibas, Yaniv Fogel, and Meir Feder · 2019
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