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Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization
12 August 2024
Holger Boche
Vít Fojtík
Adalbert Fono
Gitta Kutyniok
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Papers citing
"Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization"
2 / 2 papers shown
Title
Learning ReLU networks to high uniform accuracy is intractable
Julius Berner
Philipp Grohs
F. Voigtlaender
19
4
0
26 May 2022
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
219
1,818
0
03 Feb 2017
1