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  4. Cited By
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

7 January 2021
Burak Bartan
Mert Pilanci
ArXiv (abs)PDFHTML

Papers citing "Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization of Polynomial Activation Neural Networks in Fully Polynomial-Time"

10 / 10 papers shown
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture
Yikun Hou
Suvrit Sra
A. Yurtsever
403
0
0
27 Jan 2025
Least Squares Training of Quadratic Convolutional Neural Networks with
  Applications to System Theory
Least Squares Training of Quadratic Convolutional Neural Networks with Applications to System TheoryEuropean Control Conference (ECC), 2024
Zachary Yetman Van Egmond
Luis Rodrigues
97
0
0
13 Nov 2024
Adversarial Training of Two-Layer Polynomial and ReLU Activation
  Networks via Convex Optimization
Adversarial Training of Two-Layer Polynomial and ReLU Activation Networks via Convex Optimization
Daniel Kuelbs
Sanjay Lall
Mert Pilanci
AAML
195
1
0
22 May 2024
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
Analysis and Design of Quadratic Neural Networks for Regression,
  Classification, and Lyapunov Control of Dynamical Systems
Analysis and Design of Quadratic Neural Networks for Regression, Classification, and Lyapunov Control of Dynamical Systems
L. Rodrigues
S. Givigi
223
2
0
26 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
359
36
0
17 May 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
263
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
481
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
427
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
1
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