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ORCIDMichael Carbin
- > Home > Persons > Michael Carbin
Publications
- 2024
[i39]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 abs/2403.18421 (2024)- 2022
- [c34]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 - [i27]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 abs/2210.13738 (2022) - 2021
- [c32]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: 16306-16316 - [c31]Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin:
Pruning Neural Networks at Initialization: Why Are We Missing the Mark? ICLR 2021 - [c30]Jonathan S. Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit:
On the Predictability of Pruning Across Scales. ICML 2021: 9075-9083 - [i24]Rajiv Movva, Jonathan Frankle, Michael Carbin:
Studying the Consistency and Composability of Lottery Ticket Pruning Masks. CoRR abs/2104.14753 (2021) - 2020
- [c27]Alex Renda, Jonathan Frankle, Michael Carbin:
Comparing Rewinding and Fine-tuning in Neural Network Pruning. ICLR 2020 - [c26]Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin:
Linear Mode Connectivity and the Lottery Ticket Hypothesis. ICML 2020: 3259-3269 - [c24]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 - [i20]Alex Renda, Jonathan Frankle, Michael Carbin:
Comparing Rewinding and Fine-tuning in Neural Network Pruning. CoRR abs/2003.02389 (2020) - [i19]Riyadh Baghdadi, Abdelkader Nadir Debbagh, Kamel Abdous, Fatima-Zohra Benhamida, Alex Renda, Jonathan Elliott Frankle, Michael Carbin, Saman P. Amarasinghe:
TIRAMISU: A Polyhedral Compiler for Dense and Sparse Deep Learning. CoRR abs/2005.04091 (2020) - [i18]Jonathan S. Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit:
On the Predictability of Pruning Across Scales. CoRR abs/2006.10621 (2020) - [i15]Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Yang Zhang, Zhangyang Wang, Michael Carbin:
The Lottery Ticket Hypothesis for Pre-trained BERT Networks. CoRR abs/2007.12223 (2020) - [i14]Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin:
Pruning Neural Networks at Initialization: Why are We Missing the Mark? CoRR abs/2009.08576 (2020) - [i12]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 abs/2012.06908 (2020) - 2019
- [c22]Jonathan Frankle, Michael Carbin:
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks. ICLR 2019 - [i11]Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin:
The Lottery Ticket Hypothesis at Scale. CoRR abs/1903.01611 (2019) - [i9]Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy, Michael Carbin:
Linear Mode Connectivity and the Lottery Ticket Hypothesis. CoRR abs/1912.05671 (2019) - 2018
- [i8]Jonathan Frankle, Michael Carbin:
The Lottery Ticket Hypothesis: Training Pruned Neural Networks. CoRR abs/1803.03635 (2018)
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