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Research Round Up: On Anonymization -Creating Data That Enables Generalization Without Memorization
Manage episode 507884760 series 3474671
This story was originally published on HackerNoon at: https://hackernoon.com/research-round-up-on-anonymization-creating-data-that-enables-generalization-without-memorization.
Anonymization is what lets us take the most sensitive information and transform it into a safe, usable substrate for machine learning.
Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity. You can also check exclusive content about #data-privacy, #privacy, #anonymization, #privacy-enhancing-technologies, #enterprise-ai, #ai-security, #what-is-anonymization, #private-evolution, and more.
This story was written by: @yaw.etse. Learn more about this writer by checking @yaw.etse's about page, and for more stories, please visit hackernoon.com.
Anonymization is what lets us take the most sensitive information and transform it into a safe, usable substrate for machine learning. Without it, data stays locked down. With it, we can train models that are both powerful and responsible.
217 Episoden
Manage episode 507884760 series 3474671
This story was originally published on HackerNoon at: https://hackernoon.com/research-round-up-on-anonymization-creating-data-that-enables-generalization-without-memorization.
Anonymization is what lets us take the most sensitive information and transform it into a safe, usable substrate for machine learning.
Check more stories related to cybersecurity at: https://hackernoon.com/c/cybersecurity. You can also check exclusive content about #data-privacy, #privacy, #anonymization, #privacy-enhancing-technologies, #enterprise-ai, #ai-security, #what-is-anonymization, #private-evolution, and more.
This story was written by: @yaw.etse. Learn more about this writer by checking @yaw.etse's about page, and for more stories, please visit hackernoon.com.
Anonymization is what lets us take the most sensitive information and transform it into a safe, usable substrate for machine learning. Without it, data stays locked down. With it, we can train models that are both powerful and responsible.
217 Episoden
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