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2011.13550
Cited By
Tight Hardness Results for Training Depth-2 ReLU Networks
Information Technology Convergence and Services (ITCS), 2020
27 November 2020
Surbhi Goel
Adam R. Klivans
Pasin Manurangsi
Daniel Reichman
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Papers citing
"Tight Hardness Results for Training Depth-2 ReLU Networks"
29 / 29 papers shown
The Computational Complexity of Counting Linear Regions in ReLU Neural Networks
Moritz Stargalla
Christoph Hertrich
Daniel Reichman
MLT
511
2
0
22 May 2025
On the Expressiveness of Rational ReLU Neural Networks With Bounded Depth
International Conference on Learning Representations (ICLR), 2025
Gennadiy Averkov
Christopher Hojny
Maximilian Merkert
442
9
0
10 Feb 2025
Generalizability of Memorization Neural Networks
Lijia Yu
Xiao-Shan Gao
Lijun Zhang
Yibo Miao
296
1
0
01 Nov 2024
Absence of Closed-Form Descriptions for Gradient Flow in Two-Layer Narrow Networks
Yeachan Park
AI4CE
237
0
0
15 Aug 2024
Linear Bellman Completeness Suffices for Efficient Online Reinforcement Learning with Few Actions
Noah Golowich
Ankur Moitra
OffRL
329
3
0
17 Jun 2024
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
International Conference on Machine Learning (ICML), 2024
Sungyoon Kim
Mert Pilanci
588
10
0
06 Feb 2024
Polynomial-Time Solutions for ReLU Network Training: A Complexity Classification via Max-Cut and Zonotopes
Yifei Wang
Mert Pilanci
276
3
0
18 Nov 2023
Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning
Yingcong Li
Kartik K. Sreenivasan
Angeliki Giannou
Dimitris Papailiopoulos
Samet Oymak
LRM
310
21
0
30 May 2023
Complexity of Neural Network Training and ETR: Extensions with Effectively Continuous Functions
AAAI Conference on Artificial Intelligence (AAAI), 2023
Teemu Hankala
Miika Hannula
J. Kontinen
Jonni Virtema
193
6
0
19 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
788
47
0
29 Apr 2023
Training Neural Networks is NP-Hard in Fixed Dimension
Neural Information Processing Systems (NeurIPS), 2023
Vincent Froese
Christoph Hertrich
345
22
0
29 Mar 2023
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron
International Conference on Machine Learning (ICML), 2023
Jingfeng Wu
Difan Zou
Zixiang Chen
Vladimir Braverman
Quanquan Gu
Sham Kakade
323
9
0
03 Mar 2023
Lower Bounds on the Depth of Integral ReLU Neural Networks via Lattice Polytopes
International Conference on Learning Representations (ICLR), 2023
Christian Haase
Christoph Hertrich
Georg Loho
283
31
0
24 Feb 2023
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy
Neural Information Processing Systems (NeurIPS), 2023
Amit Daniely
Nathan Srebro
Gal Vardi
281
8
0
15 Feb 2023
A Combinatorial Perspective on the Optimization of Shallow ReLU Networks
Neural Information Processing Systems (NeurIPS), 2022
Michael Matena
Colin Raffel
273
3
0
01 Oct 2022
Training Fully Connected Neural Networks is
∃
R
\exists\mathbb{R}
∃
R
-Complete
Neural Information Processing Systems (NeurIPS), 2022
Daniel Bertschinger
Christoph Hertrich
Paul Jungeblut
Tillmann Miltzow
Simon Weber
OffRL
405
36
0
04 Apr 2022
Neural networks with linear threshold activations: structure and algorithms
Conference on Integer Programming and Combinatorial Optimization (IPCO), 2021
Sammy Khalife
Hongyu Cheng
A. Basu
587
19
0
15 Nov 2021
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
Tolga Ergen
Mert Pilanci
507
21
0
18 Oct 2021
Robust Generalization of Quadratic Neural Networks via Function Identification
Kan Xu
Hamsa Bastani
Osbert Bastani
OOD
354
9
0
22 Sep 2021
Early-stopped neural networks are consistent
Neural Information Processing Systems (NeurIPS), 2021
Ziwei Ji
Justin D. Li
Matus Telgarsky
262
50
0
10 Jun 2021
Learning a Single Neuron with Bias Using Gradient Descent
Neural Information Processing Systems (NeurIPS), 2021
Gal Vardi
Gilad Yehudai
Ohad Shamir
MLT
360
22
0
02 Jun 2021
Towards Lower Bounds on the Depth of ReLU Neural Networks
Neural Information Processing Systems (NeurIPS), 2021
Christoph Hertrich
A. Basu
M. D. Summa
M. Skutella
636
58
0
31 May 2021
The Computational Complexity of ReLU Network Training Parameterized by Data Dimensionality
Journal of Artificial Intelligence Research (JAIR), 2021
Vincent Froese
Christoph Hertrich
R. Niedermeier
355
32
0
18 May 2021
Training Neural Networks is
∃
R
\exists\mathbb R
∃
R
-complete
Mikkel Abrahamsen
Linda Kleist
Tillmann Miltzow
185
1
0
19 Feb 2021
ReLU Neural Networks of Polynomial Size for Exact Maximum Flow Computation
Conference on Integer Programming and Combinatorial Optimization (IPCO), 2021
Christoph Hertrich
Leon Sering
420
13
0
12 Feb 2021
From Local Pseudorandom Generators to Hardness of Learning
Annual Conference Computational Learning Theory (COLT), 2021
Amit Daniely
Gal Vardi
387
39
0
20 Jan 2021
Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks
Ilias Diakonikolas
D. Kane
Vasilis Kontonis
Nikos Zarifis
262
70
0
22 Jun 2020
Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size
AAAI Conference on Artificial Intelligence (AAAI), 2020
Christoph Hertrich
M. Skutella
432
28
0
28 May 2020
Principled Deep Neural Network Training through Linear Programming
D. Bienstock
Gonzalo Muñoz
Sebastian Pokutta
387
26
0
07 Oct 2018
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