关于“運用 TensorFlow Privacy 在機器學習技術中實現差異化隱私”的评价

Jimmy G. · 评论1 hour之前

Poco bien

Dua Z. · 评论1 hour之前

밤 이. · 评论4 hours之前

상태체크 안됨

Heechang H. · 评论6 hours之前

Onkar K. · 评论7 hours之前

Nikita K. · 评论8 hours之前

Saurav G. · 评论9 hours之前

The lab environment experienced several library dependency conflicts and encountered issues locating the installation path for the TensorFlow kernel. Despite successfully completing the tasks, the system fails to flag the lab as 'complete' regardless of multiple attempts. Could you please manually mark this as completed in the system? Kind regards and thank you in advance. Output: DP-SGD performed over 60000 examples with 32 examples per iteration, noise multiplier 0.5 for 1 epochs without microbatching, and no bound on number of examples per user. This privacy guarantee protects the release of all model checkpoints in addition to the final model. Example-level DP with add-or-remove-one adjacency at delta = 1e-05 computed with RDP accounting: Epsilon with each example occurring once per epoch: 10.726 Epsilon assuming Poisson sampling (*): 3.800 No user-level privacy guarantee is possible without a bound on the number of examples per user. (*) Poisson sampling is not usually done in training pipelines, but assuming that the data was randomly shuffled, it is believed the actual epsilon should be closer to this value than the conservative assumption of an arbitrary data order..

Enrique Á. · 评论9 hours之前

Heeralal Kumar S. · 评论12 hours之前

OM M. · 评论12 hours之前

Satyam V. · 评论13 hours之前

the lab is unable to monitor the progress. I'm not able to move forward

shlok p. · 评论14 hours之前

Nikitha P. · 评论14 hours之前

youngsuk kum 금. · 评论14 hours之前

Yerrannagari S. · 评论16 hours之前

Akash S. · 评论20 hours之前

Armand A. · 评论21 hours之前

Omkar S. · 评论23 hours之前

Kumari V. · 评论1 day之前

Jumple P. · 评论1 day之前

Bunny G. · 评论1 day之前

Himanshu J. · 评论1 day之前

Overall Good experience..

Vaidehi D. · 评论1 day之前

Pratik D. · 评论1 day之前

PALLAPU L. · 评论1 day之前