Abhishek Tiwari
NOVEMBER 30, 2024
Since 2009, I have published over 125 articles on this blog, creating a space where my work intersects with the rigor of academic research and the applied challenges of industry. This platform has grown beyond a personal archive. It has become a resource for researchers, industry practitioners, and students alike. It currently attracts more than 18k monthly visitor from across the globe.
The Agile Manager
NOVEMBER 30, 2024
News media have been trying to interpret the economic and commercial ramifications that will come about as a result of the US elections earlier this month. How will tariffs be used in policy and what will that mean to consumer goods prices and manufacturing supply chains? What are the risks to industrial contractors of anticipated cuts in federal government spending?
Abhishek Tiwari
NOVEMBER 30, 2024
Differential Privacy is a powerful framework for ensuring privacy in data analysis by adding controlled noise to computations. Its mathematical foundation guarantees that the presence or absence of any individual’s data in a dataset does not significantly affect the outcome of an analysis. Here are six key equations that capture the essence of differential privacy and its mechanisms, along with references to their origins and explanations.
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