Praneeth Vepakomma

发表

Supervised Dimensionality Reduction via Distance Correlation Maximization pdf

Ahmed M. Elgammal, Praneeth Vepakomma, Chetan Tonde, 2016, ArXiv.

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

Ramesh Raskar, G. N. Srinivasa Prasanna, Otkrist Gupta, 2019, ArXiv.

Diverse data selection via combinatorial quasi-concavity of distance covariance: A polynomial time global minimax algorithm

Yulia Kempner, Praneeth Vepakomma, 2019, Discret. Appl. Math..

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

Ramesh Raskar, Praneeth Vepakomma, Ken Chang, 2019, ArXiv.

DISCOMAX: A Proximity-Preserving Distance Correlation Maximization Algorithm pdf

Praneeth Vepakomma, Ahmed Elgammal, A. Elgammal, 2013, ArXiv.

Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic pdf

Ramesh Raskar, Praneeth Vepakomma, Jim Gray, 2020, ArXiv.

Acknowledgement to reviewers of JSAN in 2016

Giacomo Verticale, Szymon Szott, Farhad Shahnia, 2017 .

ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations pdf

Ramesh Raskar, Praneeth Vepakomma, Ken Chang, 2019, ArXiv.

Advances and Open Problems in Federated Learning pdf

Richard Nock, Zaïd Harchaoui, David Evans, 2019, Found. Trends Mach. Learn..

Assessing Disease Exposure Risk With Location Histories And Protecting Privacy: A Cryptographic Approach In Response To A Global Pandemic pdf

Ramesh Raskar, Praneeth Vepakomma, Kent Larson, 2020, ArXiv.

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

Ramesh Raskar, Praneeth Vepakomma, Ayush Chopra, 2020, ArXiv.

Splintering with distributions: A stochastic decoy scheme for private computation pdf

Ramesh Raskar, Praneeth Vepakomma, Julia Balla, 2020, ArXiv.

Iterative Embedding with Robust Correction using Feedback of Error Observed

Ahmed M. Elgammal, Praneeth Vepakomma, A. Elgammal, 2015, MLIS@ICML.

COVID-19 Contact-Tracing Mobile Apps: Evaluation and Assessment for Decision Makers pdf

Ramesh Raskar, Praneeth Vepakomma, Rajeev J. Surati, 2020, ArXiv.

Detailed comparison of communication efficiency of split learning and federated learning pdf

Ramesh Raskar, Otkrist Gupta, Praneeth Vepakomma, 2019, ArXiv.

Split learning for health: Distributed deep learning without sharing raw patient data pdf

Ramesh Raskar, Otkrist Gupta, Praneeth Vepakomma, 2018, ArXiv.

SplitNN-driven Vertical Partitioning pdf

Ramesh Raskar, Praneeth Vepakomma, Iker Ceballos, 2020, ArXiv.

Assessing Disease Exposure Risk with Location Data: A Proposal for Cryptographic Preservation of Privacy

Alex 'Sandy' Pentland, Praneeth Vepakomma, Kent Larson, 2020, 2003.14412.

Split Learning for collaborative deep learning in healthcare pdf

Ramesh Raskar, Praneeth Vepakomma, Ken Chang, 2019, ArXiv.

PPContactTracing: A Privacy-Preserving Contact Tracing Protocol for COVID-19 Pandemic pdf

Ramesh Raskar, Priyanka Singh, Praneeth Vepakomma, 2020, ArXiv.

A-Wristocracy: Deep learning on wrist-worn sensing for recognition of user complex activities

Sajal K. Das, Sajal K. Das, Praneeth Vepakomma, 2015, 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

Privacy-preserving collaborative deep learning methods for multiinstitutional training without sharing patient data

Ramesh Raskar, Praneeth Vepakomma, Daniel L. Rubin, 2021 .

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

Ramesh Raskar, Otkrist Gupta, Praneeth Vepakomma, 2020, 2020 International Conference on Data Mining Workshops (ICDMW).

Privacy in Deep Learning: A Survey pdf

Ramesh Raskar, Abhishek Singh, Praneeth Vepakomma, 2020, ArXiv.

A survey of nature-inspired algorithms for feature selection to identify Parkinson's disease

Anupam Shukla, Praneeth Vepakomma, Neera Bhansali, 2017, Comput. Methods Programs Biomed..

No Peek: A Survey of private distributed deep learning pdf

Ramesh Raskar, Abhimanyu Dubey, Otkrist Gupta, 2018, ArXiv.

A Review of Homomorphic Encryption Libraries for Secure Computation pdf

Ramesh Raskar, Praneeth Vepakomma, Santanu Bhattacharya, 2018, ArXiv.

FedML: A Research Library and Benchmark for Federated Machine Learning pdf

Ramesh Raskar, Yang Liu, Xiaoyang Wang, 2020, ArXiv.

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

Ramesh Raskar, Praneeth Vepakomma, Tristan Swedish, 2019, ArXiv.

Advances and Open Problems in Federated Learning

Richard Nock, Zaïd Harchaoui, Mehdi Bennis, 2021, Found. Trends Mach. Learn..

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

Ramesh Raskar, Praneeth Vepakomma, Ayush Chopra, 2020, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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

Ramesh Raskar, Yulia Kempner, Praneeth Vepakomma, 2021, ArXiv.

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

Mehdi Bennis, Ramesh Raskar, Praneeth Vepakomma, 2021, 2021 IEEE Global Communications Conference (GLOBECOM).

Differentially Private Supervised Manifold Learning with Applications like Private Image Retrieval pdf

Ramesh Raskar, Praneeth Vepakomma, Julia Balla, 2021, ArXiv.

PrivateMail: Supervised Manifold Learning of Deep Features with Privacy for Image Retrieval

Ramesh Raskar, Praneeth Vepakomma, Julia Balla, 2021, AAAI.

A fast algorithm for manifold learning by posing it as a symmetric diagonally dominant linear system

Praneeth Vepakomma, Ahmed Elgammal, 2016 .