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Differential Privacy: A Primer
Differential Privacy (DP) is a mathematical framework that protects individual privacy in data …
Mathematical Guarantee
A mathematical guarantee is a formal, provable assurance about the behavior, performance, or …
The funnel of relevance
Anyone who has worked with advanced search systems knows the intricacy of boolean operators. AND, …
What is worth of your data to LLM?
When a machine learning model is trained on a dataset, not all data points contribute equally to the …
Microservice Architecture of Meta
Microservices have become the dominant architectural paradigm for building large-scale distributed …
Modelling data flows as graphs to apply user privacy constraint
Personal data processing forms the backbone of many big tech service providers. Tech giants like …
Pre-Deployment Policy Compliance
The ability to deploy applications quickly and efficiently is crucial for organizations. Agile …
Upcoming of the learned data structures
Can machine learning-based data structures i.e. learned data structures replace traditional data …
Bias and Fairness in Machine Learning
In AI and machine learning, the future resembles the past and bias refers to prior information. …