Jonathan Frankle

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 55

Top Topics

Data Dimensionality

Biomedical Text

Top Venues

Publications

Cody Blakeney, Mansheej Paul, Brett W. Larsen, Sean Owen, Jonathan Frankle
Does your data spark joy? Performance gains from domain upsampling at the end of training. CoRR (2024)
Nikhil Sardana, Jonathan Frankle
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws. CoRR (2024)
Zachary Ankner, Naomi Saphra, Davis W. Blalock, Jonathan Frankle, Matthew L. Leavitt
Dynamic Masking Rate Schedules for MLM Pretraining. EACL (2) (2024)
Devin Kwok, Nikhil Anand, Jonathan Frankle, Gintare Karolina Dziugaite, David Rolnick
Dataset Difficulty and the Role of Inductive Bias. CoRR (2024)
Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, David Hall, Betty Xiong, Tony Lee, Roxana Daneshjou, Jonathan Frankle, Percy Liang, Michael Carbin, Christopher D. Manning
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text. CoRR (2024)
Dan Biderman, Jose Javier Gonzalez Ortiz, Jacob Portes, Mansheej Paul, Philip Greengard, Connor Jennings, Daniel King, Sam Havens, Vitaliy Chiley, Jonathan Frankle, Cody Blakeney, John P. Cunningham
LoRA Learns Less and Forgets Less. CoRR (2024)
Jacob Portes, Alexander Trott, Sam Havens, Daniel King, Abhinav Venigalla, Moin Nadeem, Nikhil Sardana, Daya Khudia, Jonathan Frankle
MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining. NeurIPS (2023)
Jacob Portes, Alex Trott, Sam Havens, Daniel King, Abhinav Venigalla, Moin Nadeem, Nikhil Sardana, Daya Khudia, Jonathan Frankle
MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining. CoRR (2023)
Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov
CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images. CoRR (2023)
Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite
Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? ICLR (2023)
Xingyu Liu, Alex Leonardi, Lu Yu, Chris Gilmer-Hill, Matthew L. Leavitt, Jonathan Frankle
Knowledge Distillation for Efficient Sequences of Training Runs. CoRR (2023)
Zachary Ankner, Naomi Saphra, Davis W. Blalock, Jonathan Frankle, Matthew L. Leavitt
Dynamic Masking Rate Schedules for MLM Pretraining. CoRR (2023)
A. Feder Cooper, Katherine Lee, James Grimmelmann, Daphne Ippolito, Christopher Callison-Burch, Christopher A. Choquette-Choo, Niloofar Mireshghallah, Miles Brundage, David Mimno, Madiha Zahrah Choksi, Jack M. Balkin, Nicholas Carlini, Christopher De Sa, Jonathan Frankle, Deep Ganguli, Bryant Gipson, Andres Guadamuz, Swee Leng Harris, Abigail Z. Jacobs, Elizabeth Joh, Gautam Kamath, Mark Lemley, Cass Matthews, Christine McLeavey, Corynne McSherry, Milad Nasr, Paul Ohm, Adam Roberts, Tom Rubin, Pamela Samuelson, Ludwig Schubert, Kristen Vaccaro, Luis Villa, Felix Wu, Elana Zeide
Report of the 1st Workshop on Generative AI and Law. CoRR (2023)
A. Feder Cooper, Jonathan Frankle, Christopher De Sa
Non-Determinism and the Lawlessness of ML Code. CoRR (2022)
A. Feder Cooper, Jonathan Frankle, Christopher De Sa
Non-Determinism and the Lawlessness of Machine Learning Code. CSLAW (2022)
Tian Jin, Michael Carbin, Daniel M. Roy, Jonathan Frankle, Gintare Karolina Dziugaite
Pruning's Effect on Generalization Through the Lens of Training and Regularization. NeurIPS (2022)
Zachary Ankner, Alex Renda, Gintare Karolina Dziugaite, Jonathan Frankle, Tian Jin
The Effect of Data Dimensionality on Neural Network Prunability. CoRR (2022)
Tiffany J. Vlaar, Jonathan Frankle
What Can Linear Interpolation of Neural Network Loss Landscapes Tell Us? ICML (2022)
Mansheej Paul, Feng Chen, Brett W. Larsen, Jonathan Frankle, Surya Ganguli, Gintare Karolina Dziugaite
Unmasking the Lottery Ticket Hypothesis: What's Encoded in a Winning Ticket's Mask? CoRR (2022)
Andi Peng, Jessica Zosa Forde, Yonadav Shavit, Jonathan Frankle
Strengthening Subcommunities: Towards Sustainable Growth in AI Research. CoRR (2022)
Cody Blakeney, Jessica Zosa Forde, Jonathan Frankle, Ziliang Zong, Matthew L. Leavitt
Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation. CoRR (2022)
Jacob Portes, Davis W. Blalock, Cory Stephenson, Jonathan Frankle
Fast Benchmarking of Accuracy vs. Training Time with Cyclic Learning Rates. CoRR (2022)
Mansheej Paul, Brett W. Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite
Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. CoRR (2022)
Tian Jin, Michael Carbin, Daniel M. Roy, Jonathan Frankle, Gintare Karolina Dziugaite
Pruning's Effect on Generalization Through the Lens of Training and Regularization. CoRR (2022)
Mansheej Paul, Brett W. Larsen, Surya Ganguli, Jonathan Frankle, Gintare Karolina Dziugaite
Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks. NeurIPS (2022)
Jose Javier Gonzalez Ortiz, Jonathan Frankle, Mike Rabbat, Ari S. Morcos, Nicolas Ballas
Trade-offs of Local SGD at Scale: An Empirical Study. CoRR (2021)
Rajiv Movva, Jonathan Frankle, Michael Carbin
Studying the Consistency and Composability of Lottery Ticket Pruning Masks. CoRR (2021)
Jonathan S. Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit
On the Predictability of Pruning Across Scales. ICML (2021)
Tiffany Vlaar, Jonathan Frankle
What can linear interpolation of neural network loss landscapes tell us? CoRR (2021)
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel Roy, Michael Carbin
Pruning Neural Networks at Initialization: Why Are We Missing the Mark? ICLR (2021)
Jonathan Frankle, David J. Schwab, Ari S. Morcos
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs. ICLR (2021)
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang
The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models. CVPR (2021)
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Michael Carbin, Zhangyang Wang
The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models. CoRR (2020)
Jonathan Frankle
Revisiting "Qualitatively Characterizing Neural Network Optimization Problems". CoRR (2020)
Jonathan S. Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit
On the Predictability of Pruning Across Scales. CoRR (2020)
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
Linear Mode Connectivity and the Lottery Ticket Hypothesis. ICML (2020)
Jonathan Frankle, David J. Schwab, Ari S. Morcos
Training BatchNorm and Only BatchNorm: On the Expressive Power of Random Features in CNNs. CoRR (2020)
Alex Renda, Jonathan Frankle, Michael Carbin
Comparing Rewinding and Fine-tuning in Neural Network Pruning. ICLR (2020)
Alex Renda, Jonathan Frankle, Michael Carbin
Comparing Rewinding and Fine-tuning in Neural Network Pruning. CoRR (2020)
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
Pruning Neural Networks at Initialization: Why are We Missing the Mark? CoRR (2020)
Davis W. Blalock, Jose Javier Gonzalez Ortiz, Jonathan Frankle, John V. Guttag
What is the State of Neural Network Pruning? CoRR (2020)
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin
The Lottery Ticket Hypothesis for Pre-trained BERT Networks. NeurIPS (2020)
Davis W. Blalock, Jose Javier Gonzalez Ortiz, Jonathan Frankle, John V. Guttag
What is the State of Neural Network Pruning? MLSys (2020)
Jonathan Frankle, David J. Schwab, Ari S. Morcos
The Early Phase of Neural Network Training. ICLR (2020)
Jonathan Frankle, David J. Schwab, Ari S. Morcos
The Early Phase of Neural Network Training. CoRR (2020)
Tiffany Tianhui Cai, Jonathan Frankle, David J. Schwab, Ari S. Morcos
Are all negatives created equal in contrastive instance discrimination? CoRR (2020)
Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin
The Lottery Ticket Hypothesis for Pre-trained BERT Networks. CoRR (2020)
Jonathan Frankle, David Bau
Dissecting Pruned Neural Networks. CoRR (2019)
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
Linear Mode Connectivity and the Lottery Ticket Hypothesis. CoRR (2019)
Jonathan Frankle, Michael Carbin
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks. ICLR (2019)
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin
The Lottery Ticket Hypothesis at Scale. CoRR (2019)
Jonathan Frankle, Sunoo Park, Daniel Shaar, Shafi Goldwasser, Daniel J. Weitzner
Practical Accountability of Secret Processes. IACR Cryptol. ePrint Arch. 2018 (2018)
Jonathan Frankle, Sunoo Park, Daniel Shaar, Shafi Goldwasser, Daniel J. Weitzner
Practical Accountability of Secret Processes. USENIX Security Symposium (2018)
Jonathan Frankle, Michael Carbin
The Lottery Ticket Hypothesis: Training Pruned Neural Networks. CoRR (2018)
Jonathan Frankle, Peter-Michael Osera, David Walker, Steve Zdancewic
Example-directed synthesis: a type-theoretic interpretation. POPL (2016)
Jonathan Frankle
Type-Directed Synthesis of Products. CoRR (2015)