Praneeth Vepakomma
Orcid: 0000-0003-2296-9296
According to our database1,
Praneeth Vepakomma
authored at least 47 papers
between 2015 and 2024.
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Bibliography
2024
CoRR, 2024
2023
Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric.
Trans. Mach. Learn. Res., 2023
Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Parallel Quasi-Concave Set Function Optimization for Scalability Even Without Submodularity.
Proceedings of the IEEE High Performance Extreme Computing Conference, 2023
2022
Visual Transformer Meets CutMix for Improved Accuracy, Communication Efficiency, and Data Privacy in Split Learning.
CoRR, 2022
The Privacy-Welfare Trade-off: Effects of Differential Privacy on Influence & Welfare in Social Choice.
CoRR, 2022
LocFedMix-SL: Localize, Federate, and Mix for Improved Scalability, Convergence, and Latency in Split Learning.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022
Proceedings of the 42nd IEEE International Conference on Distributed Computing Systems, 2022
Proceedings of the Computer Vision - ECCV 2022, 2022
Blind Inference: An Automated Privacy-Preserving Prediction Service using Secure Multi-Party Computation for Medical Applications.
Proceedings of the AMIA 2022, 2022
PrivateMail: Supervised Manifold Learning of Deep Features with Privacy for Image Retrieval.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Split Learning: A Resource Efficient Model and Data Parallel Approach for Distributed Deep Learning.
Proceedings of the Federated Learning, 2022
2021
Server-Side Local Gradient Averaging and Learning Rate Acceleration for Scalable Split Learning.
CoRR, 2021
CoRR, 2021
Private measurement of nonlinear correlations between data hosted across multiple parties.
CoRR, 2021
Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity.
CoRR, 2021
Differentially Private Supervised Manifold Learning with Applications like Private Image Retrieval.
CoRR, 2021
AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning.
Proceedings of the IEEE Global Communications Conference, 2021
NoPeek-Infer: Preventing face reconstruction attacks in distributed inference after on-premise training.
Proceedings of the 16th IEEE International Conference on Automatic Face and Gesture Recognition, 2021
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
2020
PPContactTracing: A Privacy-Preserving Contact Tracing Protocol for COVID-19 Pandemic.
CoRR, 2020
CoRR, 2020
Assessing Disease Exposure Risk With Location Histories And Protecting Privacy: A Cryptographic Approach In Response To A Global Pandemic.
CoRR, 2020
NoPeek: Information leakage reduction to share activations in distributed deep learning.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020
2019
Diverse data selection via combinatorial quasi-concavity of distance covariance: A polynomial time global minimax algorithm.
Discret. Appl. Math., 2019
ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations.
CoRR, 2019
ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries.
CoRR, 2019
Maximal adversarial perturbations for obfuscation: Hiding certain attributes while preserving rest.
CoRR, 2019
Detailed comparison of communication efficiency of split learning and federated learning.
CoRR, 2019
2018
Split learning for health: Distributed deep learning without sharing raw patient data.
CoRR, 2018
2017
A survey of nature-inspired algorithms for feature selection to identify Parkinson's disease.
Comput. Methods Programs Biomed., 2017
2016
CoRR, 2016
2015
Proceedings of the 4th Workshop on Machine Learning for Interactive Systems, 2015
A-Wristocracy: Deep learning on wrist-worn sensing for recognition of user complex activities.
Proceedings of the 12th IEEE International Conference on Wearable and Implantable Body Sensor Networks, 2015