OpBoost: A Vertical Federated Tree Boosting Framework Based on Order-Preserving Desensitization

1 code implementation • 4 Oct 2022 • Xiaochen Li, Yuke Hu, Weiran Liu, Hanwen Feng, Li Peng, Yuan Hong, Kui Ren, Zhan Qin

Although the solution based on Local Differential Privacy (LDP) addresses the above problems, it leads to the low accuracy of the trained model.

Privacy Preserving Vertical Federated Learning

A Capsule Network for Recommendation and Explaining What You Like and Dislike

1 code implementation • 1 Jul 2019 • Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu

A sentiment capsule architecture with a novel Routing by Bi-Agreement mechanism is proposed to identify the informative logic unit and the sentiment based representations in user-item level for rating prediction.

Knowledge Squeezed Adversarial Network Compression

no code implementations • 10 Apr 2019 • Shu Changyong, Li Peng, Xie Yuan, Qu Yanyun, Dai Longquan, Ma Lizhuang

Deep network compression has been achieved notable progress via knowledge distillation, where a teacher-student learning manner is adopted by using predetermined loss.

Knowledge Distillation Transfer Learning

SECaps: A Sequence Enhanced Capsule Model for Charge Prediction

no code implementations • 10 Oct 2018 • Congqing He, Li Peng, Yuquan Le, JiaWei He, Xiangyu Zhu

In this paper, we propose a Sequence Enhanced Capsule model, dubbed as SECaps model, to relieve this problem.