Towards Effective Tradeoff Between Content Caching and Retrieving in Dense Small Cell Network. - Xiaona Zhao; Junyu Liu; Min Sheng; Jiandong Li 001; Shuang Ni (ICC, 2020)

Improved Base Belief Function-Based Conflict Data Fusion Approach Considering Belief Entropy in the Evidence Theory. - Shuang Ni; Yan Lei; Yongchuan Tang (Entropy, 2020)

Accelerating all-electron ab initio simulation of raman spectra for biological systems. - Honghui Shang; Fang Li; Yunquan Zhang; Ying Liu; Libo Zhang; Mingchuan Wu; Yangjun Wu; Di Wei; Huimin Cui; Xin Liu 081; Fei Wang; Yuxi Ye; et al. (SC, 2021)

Joint optimization of user association and resource allocation in cache-enabled terrestrial-satellite integrating network. - Shuang Ni; Junyu Liu; Min Sheng; Jiandong Li 001; Xiaona Zhao (Sci. China Inf. Sci., 2021)

Truthful Deep Mechanism Design for Revenue-Maximization in Edge Computing With Budget Constraints. - Gang Li 028; Jun Cai 001; Shuang Ni (IEEE Trans. Veh. Technol., 2022)

Multi-perspective enhanced representation for effective session-based recommendation. - Shutong Qiao; Wei Zhou 028; Junhao Wen 001; Hongyu Wang; Linfeng Hu; Shuang Ni (Knowl. Based Syst., 2023)

Enhancing sequential recommendation with contrastive Generative Adversarial Network. - Shuang Ni; Wei Zhou 028; Junhao Wen 001; Linfeng Hu; Shutong Qiao (Inf. Process. Manag., 2023)

Adversarial learning based residual variational graph normalized autoencoder for network representation. - Zhengran Shen; Xiaoxin Guo; Bo Feng; Hangyuan Cheng; Shuang Ni; Hongliang Dong (Inf. Sci., 2023)

Enhanced contrastive learning with multi-aspect information for recommender systems. - Linfeng Hu; Wei Zhou 028; Fengji Luo; Shuang Ni; Junhao Wen 001 (Knowl. Based Syst., 2023)

Enhancing Supervised Visualization Through Autoencoder and Random Forest Proximities for Out-of-Sample Extension. - Shuang Ni; Adrien Aumon; Guy Wolf; Kevin R. Moon; Jake S. Rhodes (MLSP, 2024)

A novel multi-task learning network for skin lesion classification based on multi-modal clues and label-level fusion. - Qifeng Lin; Xiaoxin Guo; Bo Feng; Juntong Guo; Shuang Ni; Hongliang Dong (Comput. Biol. Medicine, 2024)

Intent-Driven Multi-level Augmentation with Contrastive Learning for Sequential Recommendation. - Shuang Ni; Wei Zhou 028; Fengji Luo; Yihao Zhang 002; Jun Zeng 003; Junhao Wen 001 (Knowl. Based Syst., 2025)

Random Forest Autoencoders for Guided Representation Learning. - Adrien Aumon; Shuang Ni; Myriam Lizotte; Guy Wolf; Kevin R. Moon; Jake S. Rhodes (CoRR, 2025)