no code implementations • 15 Feb 2024 • Jujia Zhao, Wenjie Wang, Chen Xu, Zhaochun Ren, See-Kiong Ng, Tat-Seng Chua
Nevertheless, applying Fed4Rec to LLM-based recommendation presents two main challenges: first, an increase in the imbalance of performance across clients, affecting the system's efficiency over time, and second, a high demand on clients' computational and storage resources for local training and inference of LLMs.
no code implementations • 13 Jan 2024 • Jujia Zhao, Wenjie Wang, Yiyan Xu, Teng Sun, Fuli Feng
In the realm of recommender systems, handling noisy implicit feedback is a prevalent challenge.
1 code implementation • 15 Dec 2023 • Xinyu Lin, Wenjie Wang, Jujia Zhao, Yongqi Li, Fuli Feng, Tat-Seng Chua
They learn a feature extractor on warm-start items to align feature representations with interactions, and then leverage the feature extractor to extract the feature representations of cold-start items for interaction prediction.