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Private measurement of nonlinear correlations between data hosted across multiple parties


Oct 19, 2021
Praneeth Vepakomma, Subha Nawer Pushpita, Ramesh Raskar


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DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks


Oct 09, 2021
Ayush Chopra, Esma Gel, Jayakumar Subramanian, Balaji Krishnamurthy, Santiago Romero-Brufau, Kalyan S. Pasupathy, Thomas C. Kingsley, Ramesh Raskar

* Accepted at Winter Simulation Conference 2021 

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Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity


Aug 19, 2021
Praneeth Vepakomma, Yulia Kempner, Ramesh Raskar

* SubSetML: Subset Selection in Machine Learning: From Theory to Practice 

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Automatic calibration of time of flight based non-line-of-sight reconstruction


May 21, 2021
Subhash Chandra Sadhu, Abhishek Singh, Tomohiro Maeda, Tristan Swedish, Ryan Kim, Lagnojita Sinha, Ramesh Raskar


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Can Self Reported Symptoms Predict Daily COVID-19 Cases?


May 18, 2021
Parth Patwa, Viswanatha Reddy, Rohan Sukumaran, Sethuraman TV, Eptehal Nashnoush, Sheshank Shankar, Rishemjit Kaur, Abhishek Singh, Ramesh Raskar


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AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning


May 02, 2021
Yusuke Koda, Jihong Park, Mehdi Bennis, Praneeth Vepakomma, Ramesh Raskar

* 6 pages, 6 figures 

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Differentially Private Supervised Manifold Learning with Applications like Private Image Retrieval


Feb 22, 2021
Praneeth Vepakomma, Julia Balla, Ramesh Raskar

* 22 pages 

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COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms


Dec 21, 2020
Rohan Sukumaran, Parth Patwa, T V Sethuraman, Sheshank Shankar, Rishank Kanaparti, Joseph Bae, Yash Mathur, Abhishek Singh, Ayush Chopra, Myungsun Kang, Priya Ramaswamy, Ramesh Raskar

* 14 pages, 16 Figures 

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DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks


Dec 20, 2020
Abhishek Singh, Ayush Chopra, Vivek Sharma, Ethan Garza, Emily Zhang, Praneeth Vepakomma, Ramesh Raskar

* Extended version of NeurIPS PPML 2020 workshop paper 

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Proximity Sensing for Contact Tracing


Sep 04, 2020
Sheshank Shankar, Ayush Chopra, Rishank Kanaparti, Myungsun Kang, Abhishek Singh, Ramesh Raskar

* The Pathcheck team's method for TC4TL challenge 

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NoPeek: Information leakage reduction to share activations in distributed deep learning


Aug 20, 2020
Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, Ramesh Raskar


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SplitNN-driven Vertical Partitioning


Aug 07, 2020
Iker Ceballos, Vivek Sharma, Eduardo Mugica, Abhishek Singh, Alberto Roman, Praneeth Vepakomma, Ramesh Raskar

* First version, please provide feedback 

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FedML: A Research Library and Benchmark for Federated Machine Learning


Jul 27, 2020
Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram, Salman Avestimehr

* We maintain the source code, documents, and user community at https://fedml.ai 

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Splintering with distributions: A stochastic decoy scheme for private computation


Jul 07, 2020
Praneeth Vepakomma, Julia Balla, Ramesh Raskar

* 28 pages, 6 figures 

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Automatic Differentiation for All Photons Imaging to See Inside Volumetric Scattering Media


Jun 02, 2020
Tomohiro Maeda, Ankit Ranjan, Ramesh Raskar


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Privacy in Deep Learning: A Survey


May 09, 2020
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh


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Privacy Guidelines for Contact Tracing Applications


Apr 28, 2020
Manish Shukla, Rajan M A, Sachin Lodha, Gautam Shroff, Ramesh Raskar

* 10 pages, 0 images 

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Split Learning for collaborative deep learning in healthcare


Dec 27, 2019
Maarten G. Poirot, Praneeth Vepakomma, Ken Chang, Jayashree Kalpathy-Cramer, Rajiv Gupta, Ramesh Raskar

* Workshop paper: 8 pages, 2 figures, 1 table 

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Advances and Open Problems in Federated Learning


Dec 10, 2019
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Keith Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaid Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konečný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao


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Recent Advances in Imaging Around Corners


Oct 12, 2019
Tomohiro Maeda, Guy Satat, Tristan Swedish, Lagnojita Sinha, Ramesh Raskar


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ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations


Oct 09, 2019
Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar

* In NeurIPS Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, 2019 

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ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries


Oct 05, 2019
Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar

* In NeurIPS Workshop on Machine learning for the Developing World (ML4D) 

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Maximal adversarial perturbations for obfuscation: Hiding certain attributes while preserving rest


Sep 27, 2019
Indu Ilanchezian, Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, G. N. Srinivasa Prasanna, Ramesh Raskar


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Detailed comparison of communication efficiency of split learning and federated learning


Sep 18, 2019
Abhishek Singh, Praneeth Vepakomma, Otkrist Gupta, Ramesh Raskar


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Data Markets to support AI for All: Pricing, Valuation and Governance


May 14, 2019
Ramesh Raskar, Praneeth Vepakomma, Tristan Swedish, Aalekh Sharan

* 7 pages, 2 figures 

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Light-Field for RF


Jan 13, 2019
Manikanta Kotaru, Guy Satat, Ramesh Raskar, Sachin Katti


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No Peek: A Survey of private distributed deep learning


Dec 08, 2018
Praneeth Vepakomma, Tristan Swedish, Ramesh Raskar, Otkrist Gupta, Abhimanyu Dubey

* 21 pages 

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