Praneeth Vepakomma

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Medeauteurs

Ramesh RaskarAssociate Professor, MIT Media LabGeverifieerd e-mailadres voor mit.edu
Bennis MehdiFull Professor, IEEE Fellow, Head of ICON, University of OuluGeverifieerd e-mailadres voor oulu.fi
Ken ChangStanford UniversityGeverifieerd e-mailadres voor stanford.edu
Salman AvestimehrDean's Professor and Director of USC-Amazon Center on Trustworthy AI, USCGeverifieerd e-mailadres voor usc.edu
Chaoyang HeCo-founder, TensorOpera AI and FedML; PhD in CS from University of Southern CaliforniaGeverifieerd e-mailadres voor usc.edu
Alex `Sandy' PentlandProfessor MITGeverifieerd e-mailadres voor mit.edu
Ahmed ElgammalRutgers UniversityGeverifieerd e-mailadres voor cs.rutgers.edu
Niloofar (Fatemeh) MireshghallahPostdoctoral scholar, University of WashingtonGeverifieerd e-mailadres voor cs.washington.edu
Nina MiolaneAssistant Professor at UC Santa BarbaraGeverifieerd e-mailadres voor ucsb.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyGeverifieerd e-mailadres voor cs.berkeley.edu
Mohammad Mohammadi AmiriAssistant Professor at Rensselaer Polytechnic InstituteGeverifieerd e-mailadres voor rpi.edu
Samuel HorvathMohamed bin Zayed University of Artificial Intelligence (MBZUAI)Geverifieerd e-mailadres voor mbzuai.ac.ae
Eduard GorbunovResearch Scientist, Mohamed bin Zayed University of Artificial IntelligenceGeverifieerd e-mailadres voor mbzuai.ac.ae
Alexey TumanovGeorgia Institute of TechnologyGeverifieerd e-mailadres voor gatech.edu
Lav R. VarshneyUniversity of Illinois Urbana-ChampaignGeverifieerd e-mailadres voor illinois.edu

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Praneeth Vepakomma

Massachusetts Institute of Technology, MBZUAI

Geverifieerd e-mailadres voor mit.edu - Homepage

Responsible AI Collaborative ML Privacy


Titel Sorteren op citaties Sorteren op jaar Sorteren op titel	Geciteerd door Geciteerd door	Jaar
Advances and open problems in federated learning P Kairouz, HB McMahan, B Avent, A Bellet, M Bennis, AN Bhagoji, ... Foundations and trends® in machine learning 14 (1–2), 1-210, 2021	7302	2021
Split Learning for Health: Distributed Deep Learning Without Sharing Raw Patient Data P Vepakomma, O Gupta, T Swedish, R Raskar	790	2019
Fedml: A research library and benchmark for federated machine learning C He, S Li, J So, M Zhang, H Wang, X Wang, P Vepakomma, A Singh, ... SpicyFL, NeurIPS 2020, 2020	518	2020
Detailed comparison of communication efficiency of split learning and federated learning A Singh, P Vepakomma, O Gupta, R Raskar https://arxiv.org/pdf/1909.09145.pdf, 2019	502*	2019
Split Learning for collaborative deep learning in healthcare MG Poirot, P Vepakomma, K Chang, J Kalpathy-Cramer, R Gupta, ...	182	2019
Privacy in Deep Learning: A Survey F Mirshghallah, M Taram, P Vepakomma, A Singh, R Raskar, ...	178	2020
A-Wristocracy: Deep Learning on Wrist-worn Sensing for Recognition of User Complex Activities P Vepakomma, D De, SK Das, S Bhansali IEEE Body Sensor Networks Conference, 2015	176	2015
Apps gone rogue: Maintaining personal privacy in an epidemic R Raskar, I Schunemann, R Barbar, K Vilcans, J Gray, P Vepakomma, ... arXiv preprint arXiv:2003.08567, 2020	146	2020
No peek: A survey of private distributed deep learning P Vepakomma, T Swedish, R Raskar, O Gupta, A and Dubey arXiv preprint arXiv:1812.03288 8, 2018	137	2018
Reducing Leakage In Distributed Deep Learning For Sensitive Health Data P Vepakomma, O Gupta, D Abhimanyu, R Raskar ICLR AI for Social Good, 2019	113	2019
Splitnn-driven vertical partitioning I Ceballos, V Sharma, E Mugica, A Singh, A Roman, P Vepakomma, ... arXiv preprint arXiv:2008.04137, 2020	94	2020
Assessing Disease Exposure Risk With Location Histories And Protecting Privacy: A Cryptographic Approach In Response To A Global Pandemic A Berke, M Bakker, P Vepakomma, R Raskar, K Larson, AS Pentland	88*	2020
Tristan Swedish, and Ramesh Raskar. 2018. Split learning for health: Distributed deep learning without sharing raw patient data P Vepakomma, O Gupta arXiv preprint arXiv:1812.00564, 2018	64	2018
A Review of Homomorphic Encryption Libraries for Secure Computation SS Sathya, P Vepakomma, R Raskar, R Ramachandra, S Bhattacharya	61	2018
LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning S Oh, J Park, P Vepakomma, S Baek, R Raskar, ... The Web Conference, (WWW 2022), 2022	52	2022
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks A Singh, A Chopra, V Sharma, E Garza, E Zhang, P Vepakomma, ... IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2021), 2021	48	2021
Supervised Dimensionality Reduction via Distance Correlation Maximization P Vepakomma, C Tonde, A Elgammal Electronic Journal of Statistics (Journal) 12 (1), 960-984, 2018	47	2018
SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models Z Lin, X Hu, Y Zhang, Z Chen, Z Fang, X Chen, A Li, P Vepakomma, ... arXiv preprint arXiv:2407.00952, 2024	32	2024
Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning S Pal, M Uniyal, J Park, P Vepakomma, R Raskar, M Bennis, M Jeon, ... arXiv preprint arXiv:2112.05929, 2022	30	2022
Adasplit: Adaptive trade-offs for resource-constrained distributed deep learning A Chopra, SK Sahu, A Singh, A Java, P Vepakomma, V Sharma, ... arXiv preprint arXiv:2112.01637, 2021	27	2021

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