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06/27/2022
Finite Littlestone Dimension Implies Finite Information Complexity
We prove that every online learnable class of functions of Littlestone d...
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11/03/2021
A Johnson–Lindenstrauss Framework for Randomly Initialized CNNs
How does the geometric representation of a dataset change after the appl...
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11/03/2021
Regularization by Misclassification in ReLU Neural Networks
We study the implicit bias of ReLU neural networks trained by a variant ...
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04/20/2020
Almost-Reed-Muller Codes Achieve Constant Rates for Random Errors
This paper considers 'δ-almost Reed-Muller codes', i.e., linear codes sp...
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07/01/2019
On Symmetry and Initialization for Neural Networks
This work provides an additional step in the theoretical understanding o...
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11/25/2018
Average-Case Information Complexity of Learning
How many bits of information are revealed by a learning algorithm for a ...
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06/14/2018
On the Perceptron's Compression
We study and provide exposition to several phenomena that are related to...
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04/16/2018
A Direct Sum Result for the Information Complexity of Learning
How many bits of information are required to PAC learn a class of hypoth...
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10/14/2017