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Deep Frank-Wolfe For Neural Network Optimization

Deep Frank-Wolfe For Neural Network Optimization

19 November 2018
Leonard Berrada
Andrew Zisserman
M. P. Kumar
    ODL
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Papers citing "Deep Frank-Wolfe For Neural Network Optimization"

7 / 7 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
94
32
0
29 Apr 2023
Compression-aware Training of Neural Networks using Frank-Wolfe
Compression-aware Training of Neural Networks using Frank-Wolfe
Max Zimmer
Christoph Spiegel
Sebastian Pokutta
29
9
0
24 May 2022
A Stochastic Bundle Method for Interpolating Networks
A Stochastic Bundle Method for Interpolating Networks
Alasdair Paren
Leonard Berrada
Rudra P. K. Poudel
M. P. Kumar
24
4
0
29 Jan 2022
Demystifying and Generalizing BinaryConnect
Demystifying and Generalizing BinaryConnect
Abhishek Sharma
Yaoliang Yu
Eyyub Sari
Mahdi Zolnouri
V. Nia
MQ
22
8
0
25 Oct 2021
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps
  and Relevance Orderings
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings
Jan Macdonald
Mathieu Besançon
Sebastian Pokutta
32
11
0
15 Oct 2021
Learning Rates as a Function of Batch Size: A Random Matrix Theory
  Approach to Neural Network Training
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training
Diego Granziol
S. Zohren
Stephen J. Roberts
ODL
37
49
0
16 Jun 2020
Safe Screening for the Generalized Conditional Gradient Method
Safe Screening for the Generalized Conditional Gradient Method
Yifan Sun
Francis R. Bach
27
9
0
22 Feb 2020
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