Jonathan Frankle

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	Toate	Din 2020
Referințe bibliografice	10428	9936
h-index	28	28
i10-index	37	36

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Michael CarbinMassachusetts Institute of TechnologyAdresă de e-mail confirmată pe csail.mit.edu
Gintare Karolina DziugaiteGoogle DeepMindAdresă de e-mail confirmată pe google.com
Daniel M. RoyResearch Director, Vector Institute; Prof., U. Toronto (Statistics, CS)Adresă de e-mail confirmată pe utoronto.ca
Jose Javier Gonzalez OrtizMassachusetts Institute of TechnologyAdresă de e-mail confirmată pe mit.edu
Ari S. MorcosDatologyAIAdresă de e-mail confirmată pe datologyai.com
Mansheej PaulResearch Scientist, DatabricksAdresă de e-mail confirmată pe databricks.com
Alex RendaPhD Student, MITAdresă de e-mail confirmată pe csail.mit.edu
Zhangyang (Atlas) WangXTX Markets & University of Texas at AustinAdresă de e-mail confirmată pe utexas.edu
Brett W. LarsenDatabricks Mosaic ResearchAdresă de e-mail confirmată pe stanford.edu
Peter-Michael OseraGrinnell CollegeAdresă de e-mail confirmată pe cs.grinnell.edu
Daniel J. Weitzner3Com Founders Senior Research Scientist, Massachusetts Institute of TechnologyAdresă de e-mail confirmată pe csail.mit.edu
Sunoo ParkMITAdresă de e-mail confirmată pe csail.mit.edu
Steve ZdancewicProfessor of Computer and Information Science, University of PennsylvaniaAdresă de e-mail confirmată pe cis.upenn.edu
David WalkerPrinceton UniversityAdresă de e-mail confirmată pe cs.princeton.edu
Jonathan S. RosenfeldPhD, Computer Science, MITAdresă de e-mail confirmată pe csail.mit.edu
Saman AmarasingheMITAdresă de e-mail confirmată pe mit.edu
Riyadh BaghdadiAssistant Professor (NYUAD); Global Network Assistant Professor (NYU); Research Affiliate (MIT)Adresă de e-mail confirmată pe nyu.edu
BENHAMIDA Fatima ZohraAssistant professor at Ecole Nationale Superieure d'InformatiqueAdresă de e-mail confirmată pe esi.dz
Abdelkader Nadir DebbaghEtudiant, Ecole Nationale Supérieure d'InformatiqueAdresă de e-mail confirmată pe esi.dz
David BauAssistant Professor at Northeastern UniversityAdresă de e-mail confirmată pe northeastern.edu

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Jonathan Frankle

Databricks

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Deep Learning


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks J Frankle, M Carbin International Conference on Learning Representations, 2019	4228	2019
What is the State of Neural Network Pruning? D Blalock, JJG Ortiz, J Frankle, J Guttag Conference on Machine Learning and Systems, 2020	1396	2020
Linear Mode Connectivity and the Lottery Ticket Hypothesis J Frankle, GK Dziugaite, DM Roy, M Carbin International Conference on Machine Learning, 2020	615	2020
Comparing Rewinding and Fine-tuning in Neural Network Pruning A Renda, J Frankle, M Carbin International Conference on Learning Representations, 2020	460	2020
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	410	2020
The Perpetual Line-Up: Unregulated Police Face Recognition in America C Garvie, A Bedoya, J Frankle Georgetown Law, Center on Privacy & Technology, 2016	406	2016
Stabilizing the Lottery Ticket Hypothesis / The Lottery Ticket Hypothesis at Scale J Frankle, GK Dziugaite, DM Roy, M Carbin arXiv, 2019	391*	2019
Introducing MPT-7B: A New Standard for Open-Source, Commercially Usable LLMs MMLNLP Team https://www.databricks.com/blog/mpt-7b, 2023	281*	2023
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	267	2021
The lottery ticket hypothesis: Training pruned neural networks J Frankle, M Carbin arXiv preprint arXiv:1803.03635 2, 2018	202	2018
The Early Phase of Neural Network Training J Frankle, DJ Schwab, AS Morcos International Conference on Learning Representations, 2020	192	2020
Example-Directed Synthesis: A Type-Theoretic Interpretation J Frankle, PM Osera, D Walker, S Zdancewic POPL 51 (1), 802-815, 2016	156	2016
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	146	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 Conference on Computer Vision and Pattern Recognition, 2021	142	2021
Facial-Recognition Software Might Have a Racial Bias Problem C Garvie, J Frankle The Atlantic 7, 2016	136	2016
Lora learns less and forgets less D Biderman, J Portes, JJG Ortiz, M Paul, P Greengard, C Jennings, ... Transactions on Machine Learning Research, 2024	104	2024
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	93	2018
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	92*	2021
The shift from models to compound ai systems M Zaharia, O Khattab, L Chen, JQ Davis, H Miller, C Potts, J Zou, ... Berkeley Artificial Intelligence Research Lab. Available online at: https …, 2024	73	2024
Desirable Inefficiency P Ohm, J Frankle Fla. L. Rev. 70, 777, 2018	73	2018

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