1 citations · 1 across the 8 of their papers we have counts for
Showing 2024Show all
3 papers · 1 filter
cs.LG2024
Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption
Zhizheng Lai, Yufei Zhou, Peijia Zheng +1
The recently proposed Kolmogorov-Arnold Networks (KANs) offer enhanced interpretability and greater model expressiveness. However, KANs also present challenges related to privacy l…
cs.LG2024
Optimistic Rates for Learning from Label Proportions
Gene Li, Lin Chen, Adel Javanmard +1
We consider a weakly supervised learning problem called Learning from Label Proportions (LLP), where examples are grouped into ``bags'' and only the average label within each bag i…
cs.LG2024
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions
Adel Javanmard, Lin Chen, Vahab Mirrokni +2
Due to the rise of privacy concerns, in many practical applications the training data is aggregated before being shared with the learner, in order to protect privacy of users' sens…