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- ArticleOctober 2024
Efficient Large-Scale Multi-party Computation Based on Garbled Circuit
Information Security Practice and ExperiencePages 240–257https://doi.org/10.1007/978-981-97-9053-1_14AbstractMulti-party garbled circuits employ distributed garbling strategy to achieve constant-round secure computation and authentication techniques to resist malicious adversaries. Implementations of these multi-party authenticated garbled circuits are ...
- ArticleAugust 2024
Robust Federated Learning with Realistic Corruption
AbstractRobustness is one of the critical concerns in federated learning. Existing research focuses primarily on the worst case, typically modeled as the Byzantine attack, which alters the gradients in an optimal way. However, in practice, the corruption ...
- research-articleSeptember 2024
Restructuring the Teacher and Student in Self-Distillation
IEEE Transactions on Image Processing (TIP), Volume 33Pages 5551–5563https://doi.org/10.1109/TIP.2024.3463421Knowledge distillation aims to achieve model compression by transferring knowledge from complex teacher models to lightweight student models. To reduce reliance on pre-trained teacher models, self-distillation methods utilize knowledge from the model ...
- posterSeptember 2019
Efficient multiplier-less inference of deep autoencoders on wearable healthcare systems
ISWC '19: Proceedings of the 2019 ACM International Symposium on Wearable ComputersPages 231–233https://doi.org/10.1145/3341163.3347734This paper presents an efficient multiplier-less inference (MLI) approach of deep autoencoders (DAE) for wearable healthcare systems. It employs a novel grouped multiplier block (GMB) module to reduce computational/hardwired complexity of DAE during ...