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Convex Regularization Behind Neural Reconstruction

Convex Regularization Behind Neural Reconstruction

International Conference on Learning Representations (ICLR), 2020
9 December 2020
Arda Sahiner
Morteza Mardani
Batu Mehmet Ozturkler
Mert Pilanci
John M. Pauly
ArXiv (abs)PDFHTML

Papers citing "Convex Regularization Behind Neural Reconstruction"

17 / 17 papers shown
How do Minimum-Norm Shallow Denoisers Look in Function Space?
How do Minimum-Norm Shallow Denoisers Look in Function Space?Neural Information Processing Systems (NeurIPS), 2023
Chen Zeno
Greg Ongie
Yaniv Blumenfeld
Nir Weinberger
Daniel Soudry
297
11
0
12 Nov 2023
On the Global Convergence of Natural Actor-Critic with Two-layer Neural
  Network Parametrization
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization
Mudit Gaur
Amrit Singh Bedi
Di-di Wang
Vaneet Aggarwal
301
8
0
18 Jun 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-ThresholdingIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Chunyan Xiong
Meng Lu
Xiaotong Yu
JIAN-PENG Cao
Zhong Chen
D. Guo
X. Qu
MLT
387
3
0
14 Apr 2023
Globally Optimal Training of Neural Networks with Threshold Activation
  Functions
Globally Optimal Training of Neural Networks with Threshold Activation FunctionsInternational Conference on Learning Representations (ICLR), 2023
Tolga Ergen
Halil Ibrahim Gulluk
Jonathan Lacotte
Mert Pilanci
352
10
0
06 Mar 2023
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural
  Network Parametrization
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network ParametrizationInternational Conference on Machine Learning (ICML), 2022
Mudit Gaur
Vaneet Aggarwal
Mridul Agarwal
MLT
466
3
0
14 Nov 2022
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction
GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction
Batu Mehmet Ozturkler
Arda Sahiner
Tolga Ergen
Arjun D Desai
Christopher M. Sandino
S. Vasanawala
John M. Pauly
Morteza Mardani
Mert Pilanci
228
6
0
18 Jul 2022
Unraveling Attention via Convex Duality: Analysis and Interpretations of
  Vision Transformers
Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision TransformersInternational Conference on Machine Learning (ICML), 2022
Arda Sahiner
Tolga Ergen
Batu Mehmet Ozturkler
John M. Pauly
Morteza Mardani
Mert Pilanci
364
36
0
17 May 2022
Scale-Equivariant Unrolled Neural Networks for Data-Efficient
  Accelerated MRI Reconstruction
Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI ReconstructionInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022
Beliz Gunel
Arda Sahiner
Arjun D Desai
Akshay S. Chaudhari
S. Vasanawala
Mert Pilanci
John M. Pauly
MedIm
204
9
0
21 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 DecompositionsInternational Conference on Machine Learning (ICML), 2022
Aaron Mishkin
Arda Sahiner
Mert Pilanci
OffRL
650
35
0
02 Feb 2022
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
269
12
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
486
12
0
13 Oct 2021
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models
  with Closed-Form Solutions
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
Arda Sahiner
Tolga Ergen
Batu Mehmet Ozturkler
Burak Bartan
John M. Pauly
Morteza Mardani
Mert Pilanci
GAN
432
23
0
12 Jul 2021
Training Quantized Neural Networks to Global Optimality via Semidefinite
  Programming
Training Quantized Neural Networks to Global Optimality via Semidefinite ProgrammingInternational Conference on Machine Learning (ICML), 2021
Burak Bartan
Mert Pilanci
249
10
0
04 May 2021
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex
  Optimization Models and Implicit Regularization
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit RegularizationInternational Conference on Learning Representations (ICLR), 2021
Tolga Ergen
Arda Sahiner
Batu Mehmet Ozturkler
John M. Pauly
Morteza Mardani
Mert Pilanci
473
33
0
02 Mar 2021
Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization
  of Polynomial Activation Neural Networks in Fully Polynomial-Time
Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization of Polynomial Activation Neural Networks in Fully Polynomial-Time
Burak Bartan
Mert Pilanci
180
26
0
07 Jan 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 AlgorithmsInternational Conference on Learning Representations (ICLR), 2020
Arda Sahiner
Tolga Ergen
John M. Pauly
Mert Pilanci
MLT
593
45
0
24 Dec 2020
The Hidden Convex Optimization Landscape of Two-Layer ReLU Neural
  Networks: an Exact Characterization of the Optimal Solutions
The Hidden Convex Optimization Landscape of Two-Layer ReLU Neural Networks: an Exact Characterization of the Optimal SolutionsInternational Conference on Learning Representations (ICLR), 2020
Yifei Wang
Jonathan Lacotte
Mert Pilanci
MLT
440
30
0
10 Jun 2020
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