no code implementations • 6 Apr 2023 • Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao, Weiqiang Wang, Xiaochen Li, Jinfei Liu, Zhan Qin
Knowledge Graph Embedding (KGE) is a fundamental technique that extracts expressive representation from knowledge graph (KG) to facilitate diverse downstream tasks.
no code implementations • 29 Nov 2022 • Sicong Liu, Xiaochen Li, Zimu Zhou, Bin Guo, Meng Zhang, Haochen Shen, Zhiwen Yu
We report extensive experiments on diverse datasets, scenarios, and platforms and demonstrate the superiority of AdaEnlight compared with state-of-the-art low-light image and video enhancement solutions.
1 code implementation • 14 Oct 2022 • Stone Tao, Xiaochen Li, Tongzhou Mu, Zhiao Huang, Yuzhe Qin, Hao Su
In the abstract environment, complex dynamics such as physical manipulation are removed, making abstract trajectories easier to generate.
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.
no code implementations • 4 Jun 2022 • Xiaochen Li, Xin Song, Pengjia Yuan, Xialong Liu, Yu Zhang
In this paper, we focus on a new type of user interest, i. e., user retargeting interest.
no code implementations • 25 Apr 2022 • Xiaochen Li, Rui Zhong, Jian Liang, Xialong Liu, Yu Zhang
Rich user behavior information is of great importance for capturing and understanding user interest in click-through rate (CTR) prediction.
no code implementations • 28 Oct 2021 • Xiaochen Li, Domenico Bianculli, Lionel C. Briand
Then, FITI uses a combination of rule-based and data-centric approaches, by leveraging information retrieval (IR) and machine learning (ML) techniques that analyze the words, sentences, and contexts related to an information type, to rank candidate sentences.
no code implementations • 13 May 2018 • Xiaochen Li, He Jiang, Zhilei Ren, Ge Li, Jing-Xuan Zhang
To answer these questions, we conduct a bibliography analysis on 98 research papers in SE that use deep learning techniques.
Software Engineering