5 citations · 11 across the 9 of their papers we have counts for
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Unified Kernel-Segregated Transpose Convolution Operation
Vijay Srinivas Tida, Md Imran Hossen, Liqun Shan +3
The optimization of the transpose convolution layer for deep learning applications is achieved with the kernel segregation mechanism. However, kernel segregation has disadvantages,…
Facebook Report on Privacy of fNIRS data
Md Imran Hossen, Sai Venkatesh Chilukoti, Liqun Shan +2
The primary goal of this project is to develop privacy-preserving machine learning model training techniques for fNIRS data. This project will build a local model in a centralized…
DP-SGD-Global-Adapt-V2-S: Triad Improvements of Privacy, Accuracy and Fairness via Step Decay Noise Multiplier and Step Decay Upper Clipping Threshold
Sai Venkatesh Chilukoti, Md Imran Hossen, Liqun Shan +4
Differentially Private Stochastic Gradient Descent (DP-SGD) has become a widely used technique for safeguarding sensitive information in deep learning applications. Unfortunately,…
Kernel-Segregated Transpose Convolution Operation
Vijay Srinivas Tida, Sai Venkatesh Chilukoti, Xiali Hei +1
Transpose convolution has shown prominence in many deep learning applications. However, transpose convolution layers are computationally intensive due to the increased feature map…
A Unified Training Process for Fake News Detection based on Fine-Tuned BERT Model
Vijay Srinivas Tida, Sonya Hsu, Xiali Hei
An efficient fake news detector becomes essential as the accessibility of social media platforms increases rapidly.