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Training Neural Networks is NP-Hard in Fixed Dimension

Training Neural Networks is NP-Hard in Fixed Dimension

29 March 2023
Vincent Froese
Christoph Hertrich
ArXivPDFHTML

Papers citing "Training Neural Networks is NP-Hard in Fixed Dimension"

3 / 3 papers shown
Title
Enabling Local Neural Operators to perform Equation-Free System-Level Analysis
Enabling Local Neural Operators to perform Equation-Free System-Level Analysis
Gianluca Fabiani
H. Vandecasteele
S. Goswami
Constantinos Siettos
Ioannis G. Kevrekidis
27
0
0
05 May 2025
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
86
32
0
29 Apr 2023
Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete
Training Fully Connected Neural Networks is ∃R\exists\mathbb{R}∃R-Complete
Daniel Bertschinger
Christoph Hertrich
Paul Jungeblut
Tillmann Miltzow
Simon Weber
OffRL
40
30
0
04 Apr 2022
1