Abhishek Singh

Research Assistant
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Publication

Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release

Singh, Abhishek, et al. "Posthoc privacy guarantees for collaborative inference with modified Propose-Test-Release." Thirty-seventh Conference on Neural Information Processing Systems. 2023.

Publication

Formal privacy guarantees for neural network queries by estimating local Lipschitz constant

Formal Privacy Guarantees for Neural Network queries by estimating local Lipschitz constant

Publication

NoPeek-Infer: Preventing face reconstruction attacks in distributed inference after on-premise training

Praneeth Vepakomma, Abhishek Singh, Emily Zhang, Otkrist Gupta, Ramesh Raskar, IEEE International Conference on Automatic Face and Gesture Recognition (FG) 2021

Publication

FedML: A Research Library and Benchmark for Federated Machine Learning

Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Xiao Zeng, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Xinghua Zhu, Jianzong Wang, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram and Salman Avestimehr. "FedML: A Research Library and Benchmark for Federated Machine Learning." NeurIPS-SpicyFL 2020. (Baidu Best Paper Award)

Publication

DISCO: Dynamic and Invariant Sensitive Channel Obfuscation

Abhishek Singh, Ayush Chopra, Praneeth Vepakomma, Ethan Z Garza, Vivek Sharma, , Ramesh Raskar. "DISCO: Dynamic and Invariant Sensitive Channel Obfuscation." CVPR 2021

Publication

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

Indu Ilanchezian, Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, GN Prasanna, Ramesh Raskar

Publication

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

Praneeth Vepakomma, et al. "Detailed comparison of communication efficiency of split learning and federated learning." arXiv:1909.09145v1 [cs.LG] 18 Sep 2019.