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2012.13329
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Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms
International Conference on Learning Representations (ICLR), 2020
24 December 2020
Arda Sahiner
Tolga Ergen
John M. Pauly
Mert Pilanci
MLT
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Papers citing
"Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms"
33 / 33 papers shown
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Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
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Analyzing Neural Network-Based Generative Diffusion Models through Convex Optimization
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The Convex Landscape of Neural Networks: Characterizing Global Optima and Stationary Points via Lasso Models
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Mert Pilanci
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From Complexity to Clarity: Analytical Expressions of Deep Neural Network Weights via Clifford's Geometric Algebra and Convexity
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Fixing the NTK: From Neural Network Linearizations to Exact Convex Programs
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337
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On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization
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296
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0
18 Jun 2023
Optimal Sets and Solution Paths of ReLU Networks
International Conference on Machine Learning (ICML), 2023
Aaron Mishkin
Mert Pilanci
386
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31 May 2023
Variation Spaces for Multi-Output Neural Networks: Insights on Multi-Task Learning and Network Compression
Journal of machine learning research (JMLR), 2023
Joseph Shenouda
Rahul Parhi
Kangwook Lee
Robert D. Nowak
388
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25 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey
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Gonzalo Muñoz
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29 Apr 2023
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Chunyan Xiong
Meng Lu
Xiaotong Yu
JIAN-PENG Cao
Zhong Chen
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X. Qu
MLT
383
3
0
14 Apr 2023
Globally Optimal Training of Neural Networks with Threshold Activation Functions
International Conference on Learning Representations (ICLR), 2023
Tolga Ergen
Halil Ibrahim Gulluk
Jonathan Lacotte
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352
10
0
06 Mar 2023
Implicit Regularization for Group Sparsity
International Conference on Learning Representations (ICLR), 2023
Jiangyuan Li
THANH VAN NGUYEN
Chinmay Hegde
Raymond K. W. Wong
334
12
0
29 Jan 2023
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization
International Conference on Machine Learning (ICML), 2022
Mudit Gaur
Vaneet Aggarwal
Mridul Agarwal
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462
3
0
14 Nov 2022
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers
International Conference on Machine Learning (ICML), 2022
Arda Sahiner
Tolga Ergen
Batu Mehmet Ozturkler
John M. Pauly
Morteza Mardani
Mert Pilanci
352
36
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17 May 2022
Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary Optimization
European Conference on Computer Vision (ECCV), 2022
A. Yurtsever
Tolga Birdal
Vladislav Golyanik
249
15
0
23 Mar 2022
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
International Conference on Machine Learning (ICML), 2022
Aaron Mishkin
Arda Sahiner
Mert Pilanci
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639
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0
02 Feb 2022
Efficient Global Optimization of Two-Layer ReLU Networks: Quadratic-Time Algorithms and Adversarial Training
SIAM Journal on Mathematics of Data Science (SIMODS), 2022
Yatong Bai
Tanmay Gautam
Somayeh Sojoudi
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383
19
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06 Jan 2022
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
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Mert Pilanci
498
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The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program
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Parallel Deep Neural Networks Have Zero Duality Gap
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Tolga Ergen
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478
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Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs
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Mert Pilanci
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315
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11 Oct 2021
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
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Tolga Ergen
Batu Mehmet Ozturkler
Burak Bartan
John M. Pauly
Morteza Mardani
Mert Pilanci
GAN
420
22
0
12 Jul 2021
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training
American Control Conference (ACC), 2021
Yatong Bai
Tanmay Gautam
Yujie Gai
Somayeh Sojoudi
AAML
242
4
0
25 May 2021
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
International Conference on Machine Learning (ICML), 2021
Burak Bartan
Mert Pilanci
239
10
0
04 May 2021
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization
International Conference on Learning Representations (ICLR), 2021
Tolga Ergen
Arda Sahiner
Batu Mehmet Ozturkler
John M. Pauly
Morteza Mardani
Mert Pilanci
461
33
0
02 Mar 2021
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
Annual Conference Computational Learning Theory (COLT), 2021
Meena Jagadeesan
Ilya P. Razenshteyn
Suriya Gunasekar
323
22
0
24 Feb 2021
Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization of Polynomial Activation Neural Networks in Fully Polynomial-Time
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Mert Pilanci
176
26
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07 Jan 2021
Nonparametric Learning of Two-Layer ReLU Residual Units
Zhunxuan Wang
Linyun He
Chunchuan Lyu
Shay B. Cohen
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556
1
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Convex Geometry and Duality of Over-parameterized Neural Networks
Journal of machine learning research (JMLR), 2020
Tolga Ergen
Mert Pilanci
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470
67
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25 Feb 2020
Revealing the Structure of Deep Neural Networks via Convex Duality
International Conference on Machine Learning (ICML), 2020
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Mert Pilanci
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528
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Principled Deep Neural Network Training through Linear Programming
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