Archive for the '–' Category

Why You Should Think Twice Before You Click ‘Unsubscribe’ in an Email – WSJ

June 29, 2025

https://www.wsj.com/tech/cybersecurity/unsubscribe-email-security-38b40abf

Band Theory Fundamentals

June 29, 2025

https://www.numberanalytics.com/blog/band-theory-fundamentals

The great high-energy write-off – Physics World

June 29, 2025

Andersen v Weinberg
https://physicsworld.com/a/the-great-high-energy-write-off/

Holevo’s theorem

June 29, 2025

quantum mechanics – How to understand the Holevo capacity intuitively? – Physics Stack Exchange

https://physics.stackexchange.com/questions/711441/how-to-understand-the-holevo-capacity-intuitively

https://en.wikipedia.org/wiki/Holevo%27s_theorem

How Long-term Compounding Multiplies the Awesome Power of the Stock Market – The New York Times

June 29, 2025

https://www.nytimes.com/2025/06/27/business/stock-market-investing-index-funds.html

Blavatnik Awardees | Yale Ventures

June 29, 2025

https://ventures.yale.edu/programs/the-blavatnik-fund-for-innovation-at-yale/blavatnik-awardees
2025, weargenix

Your personality type: Architect (INTJ-T)

June 29, 2025

Personality type: Architect (INTJ-T)
Traits: Introverted – 82%, Intuitive – 51%, Thinking – 58%, Judging – 69%, Turbulent – 57%
Role: Analyst
Strategy: Constant Improvement

https://www.16personalities.com/intj-personality
lab roster

Understanding HOMO and LUMO | Theory, Energy Levels and More

June 29, 2025

https://www.ossila.com/pages/homo-lumo

The Limits of Differential Privacy (and Its Misuse in Data Release and Machine Learning) | July 2021 | Communications of the ACM

June 28, 2025

https://cacm.acm.org/magazines/2021/7/253460-the-limits-of-differential-privacy-and-its-misuse-in-data-release-and-machine-learning/fulltext

Differential privacy is not a silver bullet for all privacy problems. By Josep Domingo-Ferrer, David Sánchez, and Alberto Blanco-Justicia Posted Jul 1 2021

QT:{{”
The traditional approach to statistical disclosure control (SDC) for privacy protection is utility-first. Since the 1970s, national statistical institutes have been using anonymization methods with heuristic parameter choice and suitable utility preservation properties to protect data before release. Their goal is to publish analytically useful data that cannot be linked to specific respondents or leak confidential information on them.

In the late 1990s, the computer science community took another angle and proposed privacy-first data protection. In this approach a privacy model specifying an ex ante privacy condition is enforced using one or several SDC methods, such as noise addition, generalization, or microaggregation. The parameters of the SDC methods depend on the privacy model parameters, and too strict a choice of the latter may result in poor utility. The first widely accepted privacy model was k-anonymity, whereas differential privacy (DP) is the model that currently attracts the most attention.

“}}

Slipping Through My Fingers – Wikipedia

June 28, 2025

https://en.wikipedia.org/wiki/Slipping_Through_My_Fingers

From Last Day
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