運用 TensorFlow Privacy 在機器學習技術中實現差異化隱私 Reviews

Jinwook G. · Reviewed over 1 year ago

Adnan S. · Reviewed over 1 year ago

Eoin K. · Reviewed over 1 year ago

수빈 박. · Reviewed over 1 year ago

Kyoungeun L. · Reviewed over 1 year ago

지윤 임. · Reviewed over 1 year ago

Alexey S. · Reviewed over 1 year ago

현주 나. · Reviewed over 1 year ago

Hikam M. · Reviewed over 1 year ago

KIHYEON J. · Reviewed over 1 year ago

GEONWOO S. · Reviewed over 1 year ago

motioner D. · Reviewed over 1 year ago

정원 문. · Reviewed over 1 year ago

하 유. · Reviewed over 1 year ago

용성 이. · Reviewed over 1 year ago

Charlie K. · Reviewed over 1 year ago

혁 이. · Reviewed over 1 year ago

Yuchieh Cheng 鄭宇傑 E. · Reviewed over 1 year ago

Leslie M. · Reviewed over 1 year ago

Sohyun K. · Reviewed over 1 year ago

123

Emir S. · Reviewed over 1 year ago

가현 이. · Reviewed over 1 year ago

euiseok l. · Reviewed over 1 year ago

영집 김. · Reviewed over 1 year ago

Introduction to the topic of Privacy Budget was useful. However, the lab would have been more effective if the lab adopted the following approach: 1) Train the model using Privacy Budget n 2) Test the results 3) Retrain the model using Privacy Budget n+delta 4) Test the results 5) Observe the difference in model behaviour between the model using Privacy Budget n vs the model behaviour using Privacy Budget n+delta This would allow the lab user to observe that a lower privacy budget bounds more tightly an adversary's ability to improve their guess.

Paul C. · Reviewed over 1 year ago