Differential Privacy in Machine Learning with TensorFlow Privacy Reviews

Jinwook G. · Reviewed מעל שנה אחת ago

Adnan S. · Reviewed מעל שנה אחת ago

Eoin K. · Reviewed מעל שנה אחת ago

수빈 박. · Reviewed מעל שנה אחת ago

Kyoungeun L. · Reviewed מעל שנה אחת ago

지윤 임. · Reviewed מעל שנה אחת ago

Alexey S. · Reviewed מעל שנה אחת ago

현주 나. · Reviewed מעל שנה אחת ago

Hikam M. · Reviewed מעל שנה אחת ago

KIHYEON J. · Reviewed מעל שנה אחת ago

GEONWOO S. · Reviewed מעל שנה אחת ago

motioner D. · Reviewed מעל שנה אחת ago

정원 문. · Reviewed מעל שנה אחת ago

하 유. · Reviewed מעל שנה אחת ago

용성 이. · Reviewed מעל שנה אחת ago

Charlie K. · Reviewed מעל שנה אחת ago

혁 이. · Reviewed מעל שנה אחת ago

Yuchieh Cheng 鄭宇傑 E. · Reviewed מעל שנה אחת ago

Leslie M. · Reviewed מעל שנה אחת ago

Sohyun K. · Reviewed מעל שנה אחת ago

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Emir S. · Reviewed מעל שנה אחת ago

가현 이. · Reviewed מעל שנה אחת ago

euiseok l. · Reviewed מעל שנה אחת ago

영집 김. · Reviewed מעל שנה אחת 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 מעל שנה אחת ago