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Limits on representing Boolean functions by linear combinations of
  simple functions: thresholds, ReLUs, and low-degree polynomials

Limits on representing Boolean functions by linear combinations of simple functions: thresholds, ReLUs, and low-degree polynomials

26 February 2018
Richard Ryan Williams
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Papers citing "Limits on representing Boolean functions by linear combinations of simple functions: thresholds, ReLUs, and low-degree polynomials"

3 / 3 papers shown
Title
On the Depth of Monotone ReLU Neural Networks and ICNNs
On the Depth of Monotone ReLU Neural Networks and ICNNs
Egor Bakaev
Florestan Brunck
Christoph Hertrich
Daniel Reichman
Amir Yehudayoff
26
0
0
09 May 2025
Size and Depth Separation in Approximating Benign Functions with Neural
  Networks
Size and Depth Separation in Approximating Benign Functions with Neural Networks
Gal Vardi
Daniel Reichman
T. Pitassi
Ohad Shamir
23
7
0
30 Jan 2021
Benefits of depth in neural networks
Benefits of depth in neural networks
Matus Telgarsky
148
602
0
14 Feb 2016
1