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Found 12 papers, 4 papers with code
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, evaluate and agree on a group of symptoms for the elementary prognosis of pandemic diseases is enormous.
Continual Distributed Learning for Crisis Management
Social media platforms such as Twitter, Facebook etc can be utilised as an important source of information during disaster events.
When Differential Privacy Meets Interpretability: A Case Study
Given the increase in the use of personal data for training Deep Neural Networks (DNNs) in tasks such as medical imaging and diagnosis, differentially private training of DNNs is surging in importance and there is a large body of work focusing on providing better privacy-utility trade-off.
Efficient Hyperparameter Optimization for Differentially Private Deep Learning
Tuning the hyperparameters in the differentially private stochastic gradient descent (DPSGD) is a fundamental challenge.
ExCode-Mixed: Explainable Approaches towards Sentiment Analysis on Code-Mixed Data using BERT models
The increasing use of social media sites in countries like India has given rise to large volumes of code-mixed data.
Interpretability of Fine-grained Classification of Sadness and Depression
While sadness is a human emotion that people experience at certain times throughout their lives, inflicting them with emotional disappointment and pain, depression is a longer term mental illness which impairs social, occupational, and other vital regions of functioning making it a much more serious issue and needs to be catered to at the earliest.
ARLIF-IDS -- Attention augmented Real-Time Isolation Forest Intrusion Detection System
Experimental results demonstrate that the proposed attention augmented model achieves a significant reduction in execution time, by 91. 78%, and an average detection F1-Score of 0. 93 on the NSL-KDD and KDDCUP'99 dataset.
NERDA-Con: Extending NER models for Continual Learning -- Integrating Distinct Tasks and Updating Distribution Shifts
With increasing applications in areas such as biomedical information extraction pipelines and social media analytics, Named Entity Recognition (NER) has become an indispensable tool for knowledge extraction.
AdaptKeyBERT: An Attention-Based approach towards Few-Shot & Zero-Shot Domain Adaptation of KeyBERT
Downstream training for keyword extractors is a lengthy process and requires a significant amount of data.
#maskUp: Selective Attribute Encryption for Sensitive Vocalization for English language on Social Media Platforms
Vocalization of such information has allowed the investigation and identification of criminals.
Are Chatbots Ready for Privacy-Sensitive Applications? An Investigation into Input Regurgitation and Prompt-Induced Sanitization
More specifically, we find that when ChatGPT is prompted to summarize cover letters of a 100 candidates, it would retain personally identifiable information (PII) verbatim in 57. 4% of cases, and we find this retention to be non-uniform between different subgroups of people, based on attributes such as gender identity.
“Something Something Hota Hai!” An Explainable Approach towards Sentiment Analysis on Indian Code-Mixed Data
The increasing use of social media sites in countries like India has given rise to large volumes of code-mixed data.
