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07/20/2022
Fair Context-Aware Privacy Threat Modelling
Given the progressive nature of the world today, fairness is a very impo...
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07/20/2022
Can Causal (and Counterfactual) Reasoning improve Privacy Threat Modelling?
Causal questions often permeate in our day-to-day activities. With causa...
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03/20/2022
Interpretability of Fine-grained Classification of Sadness and Depression
While sadness is a human emotion that people experience at certain times...
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10/04/2021
Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning
Privacy is important considering the financial Domain as such data is hi...
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08/09/2021
Efficient Hyperparameter Optimization for Differentially Private Deep Learning
Tuning the hyperparameters in the differentially private stochastic grad...
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07/14/2021
Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning
In recent years, machine learning techniques utilizing large-scale datas...
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06/26/2021
Benchmarking Differential Privacy and Federated Learning for BERT Models
Natural Language Processing (NLP) techniques can be applied to help with...
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06/24/2021
When Differential Privacy Meets Interpretability: A Case Study
Given the increase in the use of personal data for training Deep Neural ...
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06/22/2021
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy?
Recent advances in differentially private deep learning have demonstrate...
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04/05/2021
FedPandemic: A Cross-Device Federated Learning Approach Towards Elementary Prognosis of Diseases During a Pandemic
The amount of data, manpower and capital required to understand, evaluat...
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10/06/2020
IS-CAM: Integrated Score-CAM for axiomatic-based explanations
Convolutional Neural Networks have been known as black-box models as hum...
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06/26/2020
TeleVital: Enhancing the quality of contactless health assessment
In the midst of rising positive cases of COVID-19, the hospitals face a ...
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06/25/2020
