activity
20192023
most citedLess Is Better: Unweighted Data Subsampling via Influence Function

3 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Robust Long-Tailed Learning via Label-Aware Bounded CVaR

Hong Zhu, Runpeng Yu, Xing Tang +3

Data in the real-world classification problems are always imbalanced or long-tailed, wherein the majority classes have the most of the samples that dominate the model training. In…

cs.IR2023★ 1 cited

Contrastive Multi-view Framework for Customer Lifetime Value Prediction

Chuhan Wu, Jingjie Li, Qinglin Jia +3

Accurate customer lifetime value (LTV) prediction can help service providers optimize their marketing policies in customer-centric applications. However, the heavy sparsity of cons…

cs.LG2022★ 1 cited

DIWIFT: Discovering Instance-wise Influential Features for Tabular Data

Dugang Liu, Pengxiang Cheng, Hong Zhu +6

Tabular data is one of the most common data storage formats behind many real-world web applications such as retail, banking, and e-commerce. The success of these web applications l…

cs.IR2021★ 1 cited

Non-invasive Self-attention for Side Information Fusion in Sequential Recommendation

Chang Liu, Xiaoguang Li, Guohao Cai +3

Sequential recommender systems aim to model users' evolving interests from their historical behaviors, and hence make customized time-relevant recommendations. Compared with tradit…

cs.LG2019★ 3 cited

Less Is Better: Unweighted Data Subsampling via Influence Function

Zifeng Wang, Hong Zhu, Zhenhua Dong +2

In the time of Big Data, training complex models on large-scale data sets is challenging, making it appealing to reduce data volume for saving computation resources by subsampling.…