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Jonathan Frankle
Jonathan Frankle
Databricks - Mosaic Research
Bestätigte E-Mail-Adresse bei databricks.com - Startseite
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Zitiert von
Zitiert von
Jahr
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
J Frankle, M Carbin
International Conference on Learning Representations, 2019
35492019
What is the State of Neural Network Pruning?
D Blalock, JJG Ortiz, J Frankle, J Guttag
Conference on Machine Learning and Systems, 2020
11362020
Linear Mode Connectivity and the Lottery Ticket Hypothesis
J Frankle, GK Dziugaite, DM Roy, M Carbin
International Conference on Machine Learning, 2020
4582020
Comparing Rewinding and Fine-tuning in Neural Network Pruning
A Renda, J Frankle, M Carbin
International Conference on Learning Representations, 2020
4022020
The Lottery Ticket Hypothesis for Pre-Trained BERT Networks
T Chen, J Frankle, S Chang, S Liu, Y Zhang, Z Wang, M Carbin
Neural Information Processing Systems, 2020
3532020
Stabilizing the Lottery Ticket Hypothesis / The Lottery Ticket Hypothesis at Scale
J Frankle, GK Dziugaite, DM Roy, M Carbin
arXiv, 2019
352*2019
The Perpetual Line-Up: Unregulated Police Face Recognition in America
C Garvie, A Bedoya, J Frankle
Georgetown Law, Center on Privacy & Technology, 2016
3482016
Pruning Neural Networks at Initialization: Why are We Missing the Mark?
J Frankle, GK Dziugaite, DM Roy, M Carbin
International Conference on Learning Representations, 2021
2082021
The lottery ticket hypothesis: Training pruned neural networks
J Frankle, M Carbin
arXiv preprint arXiv:1803.03635 2, 2018
1812018
The Early Phase of Neural Network Training
J Frankle, DJ Schwab, AS Morcos
International Conference on Learning Representations, 2020
1612020
Example-Directed Synthesis: A Type-Theoretic Interpretation
J Frankle, PM Osera, D Walker, S Zdancewic
POPL 51 (1), 802-815, 2016
1462016
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs
J Frankle, DJ Schwab, AS Morcos
International Conference on Learning Representations, 2021
1262021
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models
T Chen, J Frankle, S Chang, S Liu, Y Zhang, M Carbin, Z Wang
Conference on Computer Vision and Pattern Recognition, 2021
1242021
Facial-Recognition Software Might Have a Racial Bias Problem
C Garvie, J Frankle
The Atlantic 7, 2016
1242016
Practical Accountability of Secret Processes
J Frankle, S Park, D Shaar, S Goldwasser, D Weitzner
27th USENIX Security Symposium (USENIX Security 18), 657-674, 2018
852018
Are all negatives created equal in contrastive instance discrimination?
TT Cai, J Frankle, DJ Schwab, AS Morcos
Science Meets Engineering of Deep Learning Workshop (ICLR), 2021
71*2021
Desirable Inefficiency
P Ohm, J Frankle
Fla. L. Rev. 70, 777, 2018
632018
On the Predictability of Pruning Across Scales
JS Rosenfeld, J Frankle, M Carbin, N Shavit
International Conference on Machine Learning, 2021
322021
Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask?
M Paul, F Chen, BW Larsen, J Frankle, S Ganguli, GK Dziugaite
arXiv preprint arXiv:2210.03044, 2022
312022
What can linear interpolation of neural network loss landscapes tell us?
TJ Vlaar, J Frankle
International Conference on Machine Learning, 22325-22341, 2022
242022
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