28 citations · 52 across the 11 of their papers we have counts for
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cs.LG2019★ 28 cited
A New Look at an Old Problem: A Universal Learning Approach to Linear Regression
Koby Bibas, Yaniv Fogel, Meir Feder
Linear regression is a classical paradigm in statistics. A new look at it is provided via the lens of universal learning. In applying universal learning to linear regression the hy…
cs.LG2019★ 11 cited
Deep pNML: Predictive Normalized Maximum Likelihood for Deep Neural Networks
Koby Bibas, Yaniv Fogel, Meir Feder
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 ar…