Jonathan Frankle
Title
Cited by
Cited by
Year
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
J Frankle, M Carbin
International Conference on Learning Representations, 2019
1015*2019
The Perpetual Line-Up: Unregulated Police Face Recognition in America
C Garvie, A Bedoya, J Frankle
Georgetown Law, Center on Privacy & Technology, 2016
1582016
What is the State of Neural Network Pruning?
D Blalock, JJG Ortiz, J Frankle, J Guttag
Conference on Machine Learning and Systems, 2020
1172020
Stabilizing the Lottery Ticket Hypothesis / The Lottery Ticket Hypothesis at Scale
J Frankle, GK Dziugaite, DM Roy, M Carbin
arXiv, 2019
104*2019
Example-Directed Synthesis: A Type-Theoretic Interpretation
J Frankle, PM Osera, D Walker, S Zdancewic
POPL 51 (1), 802-815, 2016
952016
Comparing Rewinding and Fine-tuning in Neural Network Pruning
A Renda, J Frankle, M Carbin
International Conference on Learning Representations, 2020
502020
Facial-Recognition Software Might Have a Racial Bias Problem
C Garvie, J Frankle
The Atlantic 7, 2016
482016
Linear Mode Connectivity and the Lottery Ticket Hypothesis
J Frankle, GK Dziugaite, DM Roy, M Carbin
International Conference on Machine Learning, 2020
352020
The Early Phase of Neural Network Training
J Frankle, DJ Schwab, AS Morcos
International Conference on Learning Representations, 2020
302020
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
272018
Desirable Inefficiency
P Ohm, J Frankle
Fla. L. Rev. 70, 777, 2018
20*2018
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
182020
Why King George III Can Encrypt
W Tong, S Gold, S Gichohi, M Roman, J Frankle
Freedom to Tinker, 2014
162014
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
152021
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
9*2021
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
arXiv preprint arXiv:2012.06908, 2020
42020
Tiramisu: A polyhedral compiler for dense and sparse deep learning
R Baghdadi, AN Debbagh, K Abdous, FZ Benhamida, A Renda, ...
arXiv preprint arXiv:2005.04091, 2020
42020
Dissecting Pruned Neural Networks
J Frankle, D Bau
Workshop on Debugging Machine Learning (ICLR 2019), 2019
32019
How Russia’s new facial recognition app could end anonymity
J Frankle
The Atlantic, 2016
32016
Revisiting "Qualitatively Characterizing Neural Network Optimization Problems"
J Frankle
Workshop on Deep Learning through Information Geometry (NeurIPS 2020), 2020
22020
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Articles 1–20