OptIForest: Optimal Isolation Forest for Anomaly Detection

1 code implementation • 22 Jun 2023 • Haolong Xiang, Xuyun Zhang, Hongsheng Hu, Lianyong Qi, Wanchun Dou, Mark Dras, Amin Beheshti, Xiaolong Xu

Extensive experiments on a series of benchmarking datasets for comparative and ablation studies demonstrate that our approach can efficiently and robustly achieve better detection performance in general than the state-of-the-arts including the deep learning based methods.

Anomaly Detection Benchmarking +1

Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation

no code implementations • 17 Sep 2022 • Xiaocong Chen, Siyu Wang, Lina Yao, Lianyong Qi, Yong Li

It is more challenging to balance the exploration and exploitation in DRL RS where RS agent need to deeply explore the informative trajectories and exploit them efficiently in the context of recommender systems.

counterfactual Data Augmentation +3

Diversity-aware Web APIs Recommendation with Compatibility Guarantee

no code implementations • 10 Aug 2021 • Wenwen Gonga, Yulan Zhang, Xuyun Zhang, Yucong Duan, Yawei Wang, Yifei Chena, Lianyong Qi

Afterwards, with the diverse correlation subgraphs, we model the compatible web APIs recommendation problem to be a minimum group Steiner tree search problem.