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Neural Networks are Convex Regularizers: Exact Polynomial-time Convex
  Optimization Formulations for Two-layer Networks

Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks

24 February 2020
Mert Pilanci
Tolga Ergen
ArXivPDFHTML

Papers citing "Neural Networks are Convex Regularizers: Exact Polynomial-time Convex Optimization Formulations for Two-layer Networks"

22 / 22 papers shown
Title
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture
Yikun Hou
Suvrit Sra
A. Yurtsever
34
0
0
28 Jan 2025
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning
Jingruo Sun
Zachary Frangella
Madeleine Udell
36
0
0
28 Jan 2025
Learning with Norm Constrained, Over-parameterized, Two-layer Neural
  Networks
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks
Fanghui Liu
L. Dadi
V. Cevher
82
2
0
29 Apr 2024
Deep Reinforcement Learning: A Convex Optimization Approach
Deep Reinforcement Learning: A Convex Optimization Approach
Ather Gattami
34
0
0
29 Feb 2024
Analyzing Neural Network-Based Generative Diffusion Models through
  Convex Optimization
Analyzing Neural Network-Based Generative Diffusion Models through Convex Optimization
Fangzhao Zhang
Mert Pilanci
DiffM
51
3
0
03 Feb 2024
ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
Suzanna Parkinson
Greg Ongie
Rebecca Willett
65
6
0
24 May 2023
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
94
32
0
29 Apr 2023
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks
  with Soft-Thresholding
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding
Chunyan Xiong
Meng Lu
Xiaotong Yu
JIAN-PENG Cao
Zhong Chen
D. Guo
X. Qu
MLT
40
0
0
14 Apr 2023
Function Space and Critical Points of Linear Convolutional Networks
Function Space and Critical Points of Linear Convolutional Networks
Kathlén Kohn
Guido Montúfar
V. Shahverdi
Matthew Trager
24
11
0
12 Apr 2023
Deep Learning Meets Sparse Regularization: A Signal Processing
  Perspective
Deep Learning Meets Sparse Regularization: A Signal Processing Perspective
Rahul Parhi
Robert D. Nowak
40
25
0
23 Jan 2023
On the Implicit Bias in Deep-Learning Algorithms
On the Implicit Bias in Deep-Learning Algorithms
Gal Vardi
FedML
AI4CE
34
72
0
26 Aug 2022
Dual Convexified Convolutional Neural Networks
Dual Convexified Convolutional Neural Networks
Site Bai
Chuyang Ke
Jean Honorio
24
1
0
27 May 2022
Unraveling Attention via Convex Duality: Analysis and Interpretations of
  Vision Transformers
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers
Arda Sahiner
Tolga Ergen
Batu Mehmet Ozturkler
John M. Pauly
Morteza Mardani
Mert Pilanci
40
33
0
17 May 2022
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
Aaron Mishkin
Arda Sahiner
Mert Pilanci
OffRL
77
30
0
02 Feb 2022
Path Regularization: A Convexity and Sparsity Inducing Regularization
  for Parallel ReLU Networks
Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
Tolga Ergen
Mert Pilanci
32
16
0
18 Oct 2021
The Convex Geometry of Backpropagation: Neural Network Gradient Flows
  Converge to Extreme Points of the Dual Convex Program
The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program
Yifei Wang
Mert Pilanci
MLT
MDE
55
11
0
13 Oct 2021
Parallel Deep Neural Networks Have Zero Duality Gap
Parallel Deep Neural Networks Have Zero Duality Gap
Yifei Wang
Tolga Ergen
Mert Pilanci
79
10
0
13 Oct 2021
Global Optimality Beyond Two Layers: Training Deep ReLU Networks via
  Convex Programs
Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs
Tolga Ergen
Mert Pilanci
OffRL
MLT
32
32
0
11 Oct 2021
Practical Convex Formulation of Robust One-hidden-layer Neural Network
  Training
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training
Yatong Bai
Tanmay Gautam
Yujie Gai
Somayeh Sojoudi
AAML
24
3
0
25 May 2021
Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional
  Optimization: Sharp Analysis and Lower Bounds
Adaptive and Oblivious Randomized Subspace Methods for High-Dimensional Optimization: Sharp Analysis and Lower Bounds
Jonathan Lacotte
Mert Pilanci
20
11
0
13 Dec 2020
Nonparametric Learning of Two-Layer ReLU Residual Units
Nonparametric Learning of Two-Layer ReLU Residual Units
Zhunxuan Wang
Linyun He
Chunchuan Lyu
Shay B. Cohen
MLT
OffRL
33
1
0
17 Aug 2020
Convex Geometry and Duality of Over-parameterized Neural Networks
Convex Geometry and Duality of Over-parameterized Neural Networks
Tolga Ergen
Mert Pilanci
MLT
42
54
0
25 Feb 2020
1