FedRKG: A Privacy-preserving Federated Recommendation Framework via Knowledge Graph Enhancement

1 code implementation • 20 Jan 2024 • Dezhong Yao, Tongtong Liu, Qi Cao, Hai Jin

Federated Learning (FL) has emerged as a promising approach for preserving data privacy in recommendation systems by training models locally.

Federated Learning Privacy Preserving +1

LightBTSeg: A lightweight breast tumor segmentation model using ultrasound images via dual-path joint knowledge distillation

no code implementations • 18 Nov 2023 • Hongjiang Guo, Shengwen Wang, Hao Dang, Kangle Xiao, Yaru Yang, Wenpei Liu, Tongtong Liu, Yiying Wan

Then, the prior knowledge of benign and malignant categories is utilized to design the teacher network combined dual-path joint knowledge distillation, which distills the knowledge from cumbersome benign and malignant teachers to a lightweight student model.

Knowledge Distillation Lesion Detection +2

Tetris-inspired detector with neural network for radiation mapping

1 code implementation • 7 Feb 2023 • Ryotaro Okabe, Shangjie Xue, Jiankai Yu, Tongtong Liu, Benoit Forget, Stefanie Jegelka, Gordon Kohse, Lin-wen Hu, Mingda Li

Here we present a computational framework using Tetris-inspired detector pixels and machine learning for radiation mapping.

Multi-stage Pre-training over Simplified Multimodal Pre-training Models

1 code implementation • ACL 2021 • Tongtong Liu, Fangxiang Feng, Xiaojie Wang

Experimental results show that our method achieves comparable performance to the original LXMERT model in all downstream tasks, and even outperforms the original model in Image-Text Retrieval task.

Retrieval Sentence +1