3 papers
cs.LG2026
Efficient Analytic Uncertainty Quantification for Multi-Modal Regression
Kun Jin, James Harrison, Jiawei Li +8
Efficient uncertainty quantification (UQ) is essential for trustworthy large-scale learning. Existing UQ methods for regression tasks mainly operate under the assumption that the c…
cs.IR2025
Item-centric Exploration for Cold Start Problem
Dong Wang, Junyi Jiao, Arnab Bhadury +3
Recommender systems face a critical challenge in the item cold-start problem, which limits content diversity and exacerbates popularity bias by struggling to recommend new items. W…
cs.IR2025
Item Level Exploration Traffic Allocation in Large-scale Recommendation Systems
Dong Wang, Junyi Jiao, Arnab Bhadury +2
This paper contributes to addressing the item cold start problem in large-scale recommender systems, focusing on how to efficiently gain initial visibility for newly ingested conte…