3 papers
cs.CV2024
Data-to-Model Distillation: Data-Efficient Learning Framework
Ahmad Sajedi, Samir Khaki, Lucy Z. Liu +3
Dataset distillation aims to distill the knowledge of a large-scale real dataset into small yet informative synthetic data such that a model trained on it performs as well as a mod…
cs.CR2023
PEPSI: Practically Efficient Private Set Intersection in the Unbalanced Setting
Rasoul Akhavan Mahdavi, Nils Lukas, Faezeh Ebrahimianghazani +7
Two parties with private data sets can find shared elements using a Private Set Intersection (PSI) protocol without revealing any information beyond the intersection. Circuit PSI p…
cs.CV2023
DataDAM: Efficient Dataset Distillation with Attention Matching
Ahmad Sajedi, Samir Khaki, Ehsan Amjadian +3
Researchers have long tried to minimize training costs in deep learning while maintaining strong generalization across diverse datasets. Emerging research on dataset distillation a…