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Lottery Tickets in Linear Models: An Analysis of Iterative Magnitude
  Pruning
v1v2v3 (latest)

Lottery Tickets in Linear Models: An Analysis of Iterative Magnitude Pruning

16 July 2020
Bryn Elesedy
Varun Kanade
Yee Whye Teh
ArXiv (abs)PDFHTML

Papers citing "Lottery Tickets in Linear Models: An Analysis of Iterative Magnitude Pruning"

21 / 21 papers shown
MoreauPruner: Robust Pruning of Large Language Models against Weight
  Perturbations
MoreauPruner: Robust Pruning of Large Language Models against Weight Perturbations
Zixiao Wang
Jingwei Zhang
Wenqian Zhao
Farzan Farnia
Bei Yu
AAML
217
4
0
11 Jun 2024
Interactive Visualization of Time-Varying Flow Fields Using Particle
  Tracing Neural Networks
Interactive Visualization of Time-Varying Flow Fields Using Particle Tracing Neural Networks
Mengjiao Han
Jixian Li
Sudhanshu Sane
Shubham Gupta
Bei Wang
Steve Petruzza
C. R. Johnson
AI4CE
303
4
0
20 Dec 2023
Iterative Magnitude Pruning as a Renormalisation Group: A Study in The
  Context of The Lottery Ticket Hypothesis
Iterative Magnitude Pruning as a Renormalisation Group: A Study in The Context of The Lottery Ticket Hypothesis
Abu-Al Hassan
170
0
0
06 Aug 2023
My3DGen: A Scalable Personalized 3D Generative Model
My3DGen: A Scalable Personalized 3D Generative ModelIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Luchao Qi
Jiaye Wu
Annie N. Wang
Sheng-Yu Wang
Roni Sengupta
3DH
547
7
0
11 Jul 2023
Transferability of Winning Lottery Tickets in Neural Network
  Differential Equation Solvers
Transferability of Winning Lottery Tickets in Neural Network Differential Equation Solvers
Edward Prideaux-Ghee
180
0
0
16 Jun 2023
Learning to Learn with Indispensable Connections
Learning to Learn with Indispensable Connections
Sambhavi Tiwari
Manas Gogoi
Shekhar Verma
Krishna Pratap Singh
CLL
177
1
0
06 Apr 2023
Getting Away with More Network Pruning: From Sparsity to Geometry and
  Linear Regions
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear RegionsIntegration of AI and OR Techniques in Constraint Programming (CPAIOR), 2023
Junyang Cai
Khai-Nguyen Nguyen
Nishant Shrestha
Aidan Good
Ruisen Tu
Xin Yu
Shandian Zhe
Thiago Serra
MLT
320
11
0
19 Jan 2023
Zeroth-Order Topological Insights into Iterative Magnitude Pruning
Zeroth-Order Topological Insights into Iterative Magnitude Pruning
Aishwarya H. Balwani
J. Krzyston
285
4
0
14 Jun 2022
Recall Distortion in Neural Network Pruning and the Undecayed Pruning
  Algorithm
Recall Distortion in Neural Network Pruning and the Undecayed Pruning AlgorithmNeural Information Processing Systems (NeurIPS), 2022
Aidan Good
Jia-Huei Lin
Hannah Sieg
Mikey Ferguson
Xin Yu
Shandian Zhe
J. Wieczorek
Thiago Serra
390
12
0
07 Jun 2022
Dimensionality Reduced Training by Pruning and Freezing Parts of a Deep
  Neural Network, a Survey
Dimensionality Reduced Training by Pruning and Freezing Parts of a Deep Neural Network, a SurveyArtificial Intelligence Review (Artif Intell Rev), 2022
Paul Wimmer
Jens Mehnert
Alexandru Paul Condurache
DD
390
36
0
17 May 2022
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another
  in Neural Networks
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural NetworksInternational Conference on Machine Learning (ICML), 2022
Xin Yu
Thiago Serra
Srikumar Ramalingam
Shandian Zhe
477
60
0
09 Mar 2022
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning
Yuege Xie
Bobby Shi
Hayden Schaeffer
Rachel A. Ward
293
13
0
07 Dec 2021
An Operator Theoretic View on Pruning Deep Neural Networks
An Operator Theoretic View on Pruning Deep Neural NetworksInternational Conference on Learning Representations (ICLR), 2021
William T. Redman
M. Fonoberova
Ryan Mohr
Yannis G. Kevrekidis
Igor Mezić
388
21
0
28 Oct 2021
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded
  learning
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning
Soufiane Hayou
Bo He
Gintare Karolina Dziugaite
224
2
0
22 Oct 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity
  on Pruned Neural Networks
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks
Shuai Zhang
Meng Wang
Sijia Liu
Pin-Yu Chen
Jinjun Xiong
UQCVMLT
241
15
0
12 Oct 2021
Universality of Winning Tickets: A Renormalization Group Perspective
Universality of Winning Tickets: A Renormalization Group Perspective
William T. Redman
Tianlong Chen
Zinan Lin
Akshunna S. Dogra
UQCV
342
8
0
07 Oct 2021
Heavy Tails in SGD and Compressibility of Overparametrized Neural
  Networks
Heavy Tails in SGD and Compressibility of Overparametrized Neural NetworksNeural Information Processing Systems (NeurIPS), 2021
Melih Barsbey
Romain Chor
Murat A. Erdogdu
Gaël Richard
Umut Simsekli
314
51
0
07 Jun 2021
GANs Can Play Lottery Tickets Too
GANs Can Play Lottery Tickets TooInternational Conference on Learning Representations (ICLR), 2021
Xuxi Chen
Zhenyu Zhang
Yongduo Sui
Tianlong Chen
GAN
278
61
0
31 May 2021
A Probabilistic Approach to Neural Network Pruning
A Probabilistic Approach to Neural Network PruningInternational Conference on Machine Learning (ICML), 2021
Xin-Yao Qian
Diego Klabjan
214
24
0
20 May 2021
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of
  Winning Tickets is Enough
Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is EnoughNeural Information Processing Systems (NeurIPS), 2020
Mao Ye
Lemeng Wu
Qiang Liu
186
17
0
29 Oct 2020
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization
  is Sufficient
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is SufficientNeural Information Processing Systems (NeurIPS), 2020
Ankit Pensia
Shashank Rajput
Alliot Nagle
Harit Vishwakarma
Dimitris Papailiopoulos
464
115
0
14 Jun 2020
1
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