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Global Optimality Beyond Two Layers: Training Deep ReLU Networks via
  Convex Programs
v1v2 (latest)

Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs

11 October 2021
Tolga Ergen
Mert Pilanci
    OffRLMLT
ArXiv (abs)PDFHTML

Papers citing "Global Optimality Beyond Two Layers: Training Deep ReLU Networks via Convex Programs"

11 / 11 papers shown
Title
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
160
37
0
29 Apr 2023
Piecewise Linear Neural Networks and Deep Learning
Piecewise Linear Neural Networks and Deep Learning
Qinghua Tao
Li Li
Xiaolin Huang
Xiangming Xi
Shuning Wang
Johan A. K. Suykens
43
30
0
18 Jun 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
132
33
0
17 May 2022
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs
  Locally Adaptive?
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive?
Kaiqi Zhang
Yu Wang
118
12
0
20 Apr 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
185
30
0
02 Feb 2022
Efficient Global Optimization of Two-Layer ReLU Networks: Quadratic-Time Algorithms and Adversarial Training
Efficient Global Optimization of Two-Layer ReLU Networks: Quadratic-Time Algorithms and Adversarial Training
Yatong Bai
Tanmay Gautam
Somayeh Sojoudi
AAML
112
17
0
06 Jan 2022
Neural networks with linear threshold activations: structure and
  algorithms
Neural networks with linear threshold activations: structure and algorithms
Sammy Khalife
Hongyu Cheng
A. Basu
105
16
0
15 Nov 2021
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
94
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
MLTMDE
86
11
0
13 Oct 2021
Vector-output ReLU Neural Network Problems are Copositive Programs:
  Convex Analysis of Two Layer Networks and Polynomial-time Algorithms
Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms
Arda Sahiner
Tolga Ergen
John M. Pauly
Mert Pilanci
MLT
176
44
0
24 Dec 2020
Xception: Deep Learning with Depthwise Separable Convolutions
Xception: Deep Learning with Depthwise Separable Convolutions
François Chollet
MDEBDLPINN
1.6K
14,662
0
07 Oct 2016
1