Kai Sheng

Model Sparsification for Communication-Efficient Multi-Party Learning via Contrastive Distillation in Image Classification

2023 · IEEE Transactions on Emerging Topics in Computational Intelligence

Multi-party learning allows all parties to train a joint model under legal and practical constraints without private data transmission. Related research can perform multi-party learning tasks on homogeneous data through deep networks. However, due to …