24 citations · 58 across the 16 of their papers we have counts for
13 papers
Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation
Yongjing Hao, Pengpeng Zhao, Junhua Fang +5
Sequential Recommendation (SR) has received increasing attention due to its ability to capture user dynamic preferences. Recently, Contrastive Learning (CL) provides an effective a…
Reconstructing human activities via coupling mobile phone data with location-based social networks
Le Huang, Fan Xia, Hui Chen +5
In the era of big data, the ubiquity of location-aware portable devices provides an unprecedented opportunity to understand inhabitants' behavior and their interactions with the bu…
Contrastive Enhanced Slide Filter Mixer for Sequential Recommendation
Xinyu Du, Huanhuan Yuan, Pengpeng Zhao +5
Sequential recommendation (SR) aims to model user preferences by capturing behavior patterns from their item historical interaction data. Most existing methods model user preferenc…
Adaptive Sparse Pairwise Loss for Object Re-Identification
Xiao Zhou, Yujie Zhong, Zhen Cheng +2
Object re-identification (ReID) aims to find instances with the same identity as the given probe from a large gallery. Pairwise losses play an important role in training a strong R…
Probabilistic Bilevel Coreset Selection
Xiao Zhou, Renjie Pi, Weizhong Zhang +2
The goal of coreset selection in supervised learning is to produce a weighted subset of data, so that training only on the subset achieves similar performance as training on the en…
Model Agnostic Sample Reweighting for Out-of-Distribution Learning
Xiao Zhou, Yong Lin, Renjie Pi +4
Distributionally robust optimization (DRO) and invariant risk minimization (IRM) are two popular methods proposed to improve out-of-distribution (OOD) generalization performance of…